SERA—
United States
Environmental Protection
Agency
Environmental Justice Analysis for Proposed
Supplemental Effluent Limitations Guidelines
and Standards for the Steam Electric Power
Generating Point Source Category
March 2023
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U.S. Environmental Protection Agency
Office of Water (4303T)
1200 Pennsylvania Avenue, NW
Washington, DC 20460
EPA-821-R-23-001
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Contents
1. Introduction 1
1.1 Description of the Effluent Limitations Guidelines Program 1
1.2 Steam Electric Power Generating Effluent Guidelines 1
1.3 Proposed Supplemental Effluent Limitations Guidelines and Standards for the Steam
Electric Power Generating Point Source Category 1
2. Definitions and Terminology 2
3. Executive Orders 3
4. Purpose and Outline of the Environmental Justice Analysis 4
5. Literature on Potential Environmental Justice Concerns Associated with Coal-Fired Power Plants 5
6. Nationwide Proximity Analysis 7
6.1 Socioeconomic Characteristics of Populations Residing in Proximity to Steam Electric Power
Plants 7
6.2 Socioeconomic Characteristics of Populations Served by Affected Drinking Water Systems 13
6.3 Socioeconomic Characteristics of Populations Affected by Changes in Exposure to
Pollutants in Downstream Surface Waters 19
6.4 Key Conclusions 23
7. Engagement with Communities with Potential Environmental Justice Concerns 24
7.1 Evaluating PEJC in Communities Affected by the Proposed Rule 24
7.1.1 Air Screening Analysis 24
7.1.2 Downstream Surface Water Screening Analysis 24
7.1.3 Drinking Water Screening Analysis 25
7.2 Identifying Communities with PEJC 25
7.3 Choosing Communities for Initial Outreach 26
7.3.1 Communities Chosen for Initial Outreach 27
7.4 Approach to Community Outreach 28
7.4.1 Establishing Connections with Community Representatives 28
7.4.2 Developing Outreach and Meeting Materials 28
7.4.3 Preparing for Discussions with Community Members 29
7.4.4 Designing and Scheduling Community Meetings 29
7.5 Results of the Public Meetings 30
7.5.1 Regulatory Preferences 30
7.5.2 Environmental Concerns 31
7.5.3 Human Health and Safety Concerns 33
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Contents
7.5.4 Economic Impacts 34
7.5.5 Cultural and Spiritual Impacts 35
7.5.6 Communication and Public Outreach 35
7.5.7 Concerns Relevant to Other EPA Regulatory Actions 35
8. Regulatory Options 36
8.1 FGD Wastewater 36
8.2 BA Transport Water 36
8.3 CRL 36
8.4 Legacy Wastewater 36
9. Distributional Analysis of Pollutant Exposures 38
9.1 Analysis of Exposures to Air Pollutants from Steam Electric Power Plants 38
9.1.1 Analysis of Changes in Air Quality Across Affected Areas of the Contiguous U.S 39
9.1.2 Distribution of Ozone Exposures in Communities with Predicted Changes in Air Quality
41
9.1.3 Distribution of PM2.5 Exposures in Communities with Predicted Changes in Air Quality48
9.1.4 Key Conclusions 54
9.2 Surface Water 54
9.2.1 Immediate Receiving Waters 54
9.2.2 Downstream Surface Waters 74
9.3 Drinking Water 87
9.3.1 Distribution of TTHM Exposures Among Affected Communities 88
9.3.2 Distribution of Bladder Cancer Cases Among Affected Communities 92
9.3.3 Key Conclusions 99
9.4 Cumulative Risks 100
9.4.1 Distribution of Cumulative Risks among Affected Communities 101
9.4.2 Key Conclusions 117
10. Distributional Analysis of Benefits and Costs of the Proposed Rule 118
10.1 Benefits 118
10.1.1 GHG Benefits
118
10.1.2 Conventional Air Pollutant Health Benefits 121
10.2 Costs 122
11. Limitations and Uncertainties 128
12. Conclusions 137
13. References 138
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Attachments
Appendix A: Results from the Proximity Analysis of Downstream Surface Waters
Appendix B: Results from the Screening Analyses
Appendix C: Public Outreach and Meeting Materials
Appendix D: Public Meeting Notes
Appendix E: Distributional Analysis of Neurological and Cognitive and Cancer Impacts from Pollution
in Downstream Surface Water Results
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List of Figures
Figure 1. Number of People in the Contiguous U.S. Residing in Areas with Not Changing, Changing,
Improving, and Worsening Modeled Ozone and PM2.5 Concentrations in 2030 41
Figure 2. Map of 12-km Grid Cells with Modeled Changes in MDA8 Warm Season Ozone
Concentrations-Improving (Green) or Worsening (Red)-by at Least +/-0.007 ppb in 2030 42
Figure 3. Baseline MDA8 Ozone Concentrations and Population Counts in Areas with Not Changing,
Changing, Improving, and Worsening Modeled Ozone Concentrations in 2030 43
Figure 4. Distribution of Modeled MDA8 Ozone Concentrations Across Area Categories and Selected
Population Groups in 2030 47
Figure 5. Map of 12-Kilometer Grid Cells with Modeled Average Annual PM2.5 Concentrations
Improving (Blue) or Worsening (Red) by at Least +/-0.0012 |ag/m3 in 2030 49
Figure 6. Baseline Average Annual PM2.5 Concentrations and Population Counts in Areas with Not
Changing, Changing, Improving, and Worsening Modeled Ozone Concentrations in 2030 50
Figure 7. Distribution of Modeled Annual Average PM2.5 Concentrations Across Area Categories and
Selected Population Groups in 2030 53
Figure 8. Estimated Average Annual Compliance Costs of the Proposed Rule (Option 3) per
Residential Household, by NERC Region 127
List of Tables
Table 1. Percent of the Population Living Within 1 and 3 Miles of a Steam Electric Power Plant and
Associated Immediate Receiving Reach Identifying as a Racial or Ethnic Minority or Low-Income,
Compared to the General Population 9
Table 2. Number of Affected Communities Living within 1 and 3 Miles of a Steam Electric Power Plant
and Associated Immediate Receiving Reach That Have a Higher Proportion of Individuals Who
Identify as a Racial or Ethnic Minority or Low-Income than the National Average 9
Table 3. Number of Affected Communities Living Within 1 and 3 Miles of a Steam Electric Power
Plant and Associated Immediate Receiving Reach with a Higher Proportion of Individuals Identifying
as a Racial or Ethnic Minority or Low-Income than Their State Average 10
Table 4. Socioeconomic Characteristics of the Populations of States with Communities Potentially
Affected by Steam Electric Plant Discharges, Compared to the National Average 11
Table 5. Socioeconomic Characteristics of Populations Served by Potentially Affected PWS,
Compared to the National Average 14
Table 6. Percent of the Population in Tribal Areas with an Affected PWS Identifying as Low-Income
Compared to Their Respective State Average and the National Average 17
Table 7. Percent of Population in Tribal Areas with an Affected PWS Identifying as a Racial or Ethnic
Minority Compared to Their Respective State Average and the National Average 18
Table 8. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with
Modeled Concentrations of Selected Pollutants Under the Regulatory Options Compared to the
National Average (Period 2) 20
Table 9. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with
Modeled Concentrations of Selected Pollutants Under the Regulatory Options Identifying as a Racial
or Ethnic Minority Compared to the National Average (Period 2) 21
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List of Tables
Table 10. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with
Modeled Concentrations of Selected Pollutants Under the Regulatory Options Identifying as a Racial
or Ethnic Minority Compared to the National Average (Period 2) 22
Table 11. List of Affected Communities Chosen for Initial Public Meetings Based on the Results of
EPA's Air, Surface Water, and Drinking Water Screening Analyses 27
Table 12. Regulatory Options Analyzed for the Proposed Rule 37
Table 13. Population Characteristics Included in the Ozone and PM2.5 Distributional Analyses 39
Table 14. Modeled MDA8 Ozone Concentrations (ppb) Across Area Categories and Selected
Population Groups in 2030 44
Table 15. Additional Information on the Column Headers Used in Table 14 45
Table 16. Modeled Average Annual PM2.5 Concentrations (|ag/m3) Across Area Categories and
Selected Population Groups in 2030 51
Table 17. Immediate Receiving Water Community Demographics by Water Quality Benchmark
Exceedances3 under the Baseline and Regulatory Options 56
Table 18. Immediate Receiving Water Community Demographics by Sediment Benchmark
Exceedances3 under Baseline and the Regulatory Options 59
Table 19. Immediate Receiving Water Community Demographics by NEHC Exceedances3 for Eagles
(Ingesting T4 Fish) under Baseline and the Regulatory Options 60
Table 20. Immediate Receiving Water Community Demographics by NEHC Exceedances3 for Minks
(Ingesting T3 Fish) under Baseline and the Regulatory Options 61
Table 21. Immediate Receiving Water Community Demographics by Oral RfD Exceedances3 under
Baseline and the Regulatory Options, Organized by Age and Fishing Mode Cohort 65
Table 22. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk
(LECR) Exceedances3 above 1.00 x 10-6 for Arsenic under Baseline and the Regulatory Options,
Organized by Age and Fishing Mode Cohort t 71
Table 23. Modeled Total IQ Points Under the Baseline and Change in Avoided IQ Point Losses under
the Regulatory Options Among Child Subsistence and Recreational Fish Consumers Exposed to Lead
through Fish Consumption, by Racial or Ethnic Population Group 76
Table 24. Modeled Total IQ Points under the Baseline and Change in Avoided IQ Point Losses Under
the Regulatory Options Among Child Subsistence and Recreational Fish Consumers Exposed to Lead
through Fish Consumption, by Income Group 78
Table 25. Modeled Total IQ Points Under the Baseline and Change in Avoided IQ Point Losses under
the Regulatory Options Among Child Subsistence and Recreational Fish Consumers Exposed to
Mercury through Fish Consumption, by Racial or Ethnic Population Group 80
Table 26. Modeled Total IQ Points Under the Baseline and Change in Avoided IQ Point Losses under
the Regulatory Options Among Child Subsistence and Recreational Fish Consumers Exposed to
Mercury through Fish Consumption, by Income Group 82
Table 27. Modeled Total Cancer Cases Under the Baseline and Change in Avoided Cancer Cases
under the Regulatory Options Among Adult Subsistence and Recreational Fish Consumers Exposed to
Arsenic through Fish Consumption, by Racial or Ethnic Population Group 84
Table 28. Modeled Total Cancer Cases Under the Baseline and Change in Avoided Cancer Cases
under the Regulatory Options Among Adult Subsistence and Recreational Fish Consumers Exposed to
Arsenic through Fish Consumption, by Income Group 86
Table 29. Modeled Changes in TTHM Concentrations Under the Regulatory Options Among
Potentially Affected Drinking Water Systems, by State 90
Table 30. Modeled Changes in Total Bladder Cancer Cases Avoided Under the Regulatory Options
Among Potentially Affected Drinking Water Systems, by State 94
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List of Tables
Table 31. Modeled Changes in Total Excess Bladder Cancer Deaths Avoided Under the Regulatory
Options Among Potentially Affected Drinking Water Systems, by State 97
Table 32a. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index
Exceedances3 for Cardiovascular Impacts Under Baseline and the Regulatory Options for Arsenic-
Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohort13 103
Table 32b. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index
Exceedances3 for Hematological Impacts Under Baseline and the Regulatory Options for Arsenic-
Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohort13 104
Table 32c. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index
Exceedances3 for Hematological Impacts Under Baseline and the Regulatory Options for Zinc-Lead
Mixtures, Organized by Age and Fishing Mode Cohort13 106
Table 32d. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index
Exceedances3 for Neurological Impacts Under Baseline and the Regulatory Options for Arsenic-
Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohort13 107
Table 32e. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index
Exceedances3 for Neurological Impacts Under Baseline and the Regulatory Options for
Methylmercury-Lead Mixtures, Organized by Age and Fishing Mode Cohort13 109
Table 32f. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index
Exceedances3 for Renal Impacts Under Baseline and the Regulatory Options for Arsenic-Cadmium-
Lead Mixtures, Organized by Age and Fishing Mode Cohort13 Ill
Table 33. Energy Expenditures by Quintiles of Income before Taxes, 2019 122
Table 34. Demographics by Quintiles of Income before Taxes, 2019 123
Table 35. Energy Expenditures by Race, 2019 124
Table 36. Energy Expenditures by Race or Ethnicity, 2019 125
Table 37. Limitations and Uncertainties of EPA's Proximity and Community Screening Analyses 128
Table 38. Limitations and Uncertainties of EPA's Distributional Analysis of Air Impacts 129
Table 39. Limitations and Uncertainties of EPA's Distributional Analysis of Immediate Receiving
Water Impacts 130
Table 40. Limitations and Uncertainties of EPA's Distributional Analysis of Downstream Surface
Water Impacts 132
Table 41. Limitations and Uncertainties of EPA's Distributional Analysis of Drinking Water Impacts 133
Table 42. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks 134
Table 43. Limitations and Uncertainties of EPA's Distributional Analysis of Costs and Benefits 136
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List of Abbreviations
ACS
American Community Survey
As-Cd-Pb
arsenic-cadmium-lead
APS
Arizona Public Services
ASCC
Alaska Systems Coordinating Council
ATSDR
Agency for Toxic Substances and Disease Registry
BA
bottom ash
BAT
best available technology economically achievable
BCA
benefit-cost analysis
BINWOE
binary weight-of-evidence
BMP
best management practice
BPJ
best professional judgement
BrO"
hypobromite
CAA
Clean Air Act
CBG
Census block group
CCR
coal combustion residuals
CDC
Centers for Disease Control and Prevention
CES
Consumer Expenditure Survey
CFR
Code of Federal Regulations
C02
carbon dioxide
COMID
common identifier
COPD
chronic obstructive pulmonary disease
CP
chemical precipitation
CRE
cancer risk estimate
CRL
combustion residual leachate
CWA
Clean Water Act
DBP
disinfection byproduct
D-FATE
Downstream Fate and Transport Equations
EA
environmental assessment
EAB
Environmental Appeals Board
ELGs
effluent limitations guidelines and standards
EJ
environmental justice
E.O.
Executive Order
EPA
Environmental Protection Agency
FCPP
Four Corners Power Plant
FGD
flue gas desulfurization
FRN
Federal Register Notice
GHG
greenhouse gas
GIS
geographic information system
HI
hazard index
HICC
Hawaii Coordinating Council
HQ
hazard quotient
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List of Abbreviations
HRR
high recycle rate systems
ICIS
Integrated Compliance Information System
IEUBK
integrated exposure uptake biokinetic
IPCC
Intergovernmental Panel on Climate Change
IPM
Integrated Planning Model
IQ
intelligence quotient
IRW
immediate receiving water
JTA
joint toxic action
LADD
lifetime average daily dose
LECR
lifetime excess cancer risk
LUEGU
low-utilization electric generating unit
MCL
maximum contaminant level
MCLG
maximum contaminant level goal
MDA8
maximum daily average 8-hour
Me-Hg-Pb
methyl mercury-lead
MRL
minimal risk level
MRO
Midwest Reliability Organization
NA
not applicable
NAACP
National Association for the Advancement of Colored People
NAAQS
National Ambient Air Quality Standards
NASEM
National Academies of Science, Engineering, and Medicine
NC DEQ
North Carolina Department of Environmental Quality
NEHC
no effect hazard concentration
NERC
North American Energy Reliability Corporation
NHDPIus
National Hydrography Dataset Plus
NOx
nitrogen oxides
NPCC
Northeast Power Coordinating Council
NPDES
National Pollutant Discharge Elimination System
NRWQC
National Recommended Water Quality Criteria
NS
not subcategorized
NTEC
Navajo Transitional Energy Company
OLEM
Office of Land and Emergency Management
OMB
Office of Management and Budget
OW
Office of Water
PbB
blood lead
PEJC
potential environmental justice concerns
PFAS
per- and polyfluoroalkyl substances
PM2.5
fine particulate matter
PSES
Pretreatment Standards for Existing Sources
PWS
public water systems
PWSID
public water system ID
RCRA
Resource Conservation and Recovery Act
RF
ReliabilityFirst Corporation
RfD
reference dose
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List of Abbreviations
RIA
regulatory impact analysis
SDWIS
Safe Drinking Water Information System
SERC
SERC Reliability Corporation
SI
surface impoundment
SNAP
Supplemental Nutrition Assistance Program
S02
sulfur dioxide
T3
trophic level 3
T4
trophic level 4
TDD
technical development document
TDEQ
Texas Department of Environmental Quality
TEC
threshold effect concentration
TRE
Texas Reliability Entity
THM
trihalomethane
TMDL
total maximum daily load
TTD
target organ toxicity dose
TTHM
total trihalomethanes
UCMR4
Fourth Unregulated Contaminant Monitoring Rule
USGCRP
U.S. Global Change Research Program
USGS
U.S. Geological Survey
USPS
U.S. Postal Service
WECC
Western Electricity Coordinating Council
ZCTA
Zip Code Tabulation Area
ZLD
zero liquid discharge
Zn-Pb
zinc-lead
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Executive Summary
The U.S. Environmental Protection Agency (EPA) defines environmental justice (EJ) as the "fair treatment
and meaningful involvement of all people regardless of race, color, national origin, or income with respect
to the development, implementation, and enforcement of environmental laws, regulations and policies"
(U.S. EPA, 2021). Four Executive Orders (E.O.s)- E.O. 12898, E.O. 13985, E.O. 14008, and E.O. 12866-call
on federal agencies to advance EJ and equity, in developing policies, by analyzing and addressing
disproportionately high and adverse impacts on historically underserved, marginalized, and economically
disadvantaged people.
Underthe authority of the Clean Water Act, EPA is proposing revised technology-based effluents
limitations guidelines and standards (ELGs) for the steam electric power generating point source category
for certain wastestreams. The proposed ELGs address flue gas desulfurization (FGD) wastewater, bottom
ash (BA) transport water, combustion residual leachate (CRL), and legacy wastewater at existing sources.
As research has shown, steam electric power plants are often sited in low-income and minority
communities, and as a result, these communities are often differentially exposed to and experience the
health effects from pollution from steam electric power plants compared to the average community in
the United States (NAACP, 2012; Toomey, 2013; Israel, 2012). Therefore, understanding the
socioeconomic characteristics of populations expected to be impacted by the proposed regulation is
necessary to effectively analyze whether vulnerable populations - like low-income and minority
populations - may experience disproportionately high and adverse impacts from exposures to pollutants
discharged by steam electric power plants under the baseline and to what extent the regulatory options
may mitigate, exacerbate, or create potentially disproportionately high and adverse impacts to these
populations relative to the baseline. To accomplish this, EPA conducted a distributional analysis of
pollutant exposures, health effects, and costs and benefits under the baseline and all four proposed
regulatory options across all potentially affected communities.
This analysis is divided into several core analyses. These include:
• A literature review of potential EJ concerns (PEJC) related to coal-fired power plants (Section 5).
• A national-level proximity analysis which EPA used as an initial assessment of the socioeconomic
characteristics of affected communities living in proximity to steam electric power plants, surface
waters receiving discharges from steam electric power plants, as well as affected communities served
by drinking water systems intaking water from receiving waters of steam electric power plants
(Section 6).
• A screening analysis used to identify d affected communities to prioritize for initial public outreach
(Section 7).
• A discussion of EPA's approach to planning public meetings, and the results of the public meetings
(Section 7).
L The EPA's Technical Guidance for Assessing Environmental Justice in Regulatory Analysis (2016) defines the
term disproportionate impacts as "differences in impacts or risks that are extensive enough that they may merit
Agency action. In general, the determination of whether there is a disproportionate impact that may merit
Agency action is ultimately a policy judgment which, while informed by analysis, is the responsibility of the
decision maker. The terms difference or differential indicate an analytically discernible distinction in impacts or
risks across population groups. It is the role of the analyst to assess and present differences in anticipated
impacts across population groups of concern for both the baseline and proposed regulatory options, using the
best available information (both quantitative and qualitative) to inform the decision maker and the public."
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Executive Summary
• A national-level analysis of the distribution of pollutant exposures and health effects across
population groups of concern in all potentially affected communities under the baseline and
regulatory options (Section 9). The exposure pathways, pollutant exposures, and/or human impacts
assessed include:
• Exposure to particulate matter 2.5 (PM2.5) and ozone from air pollution emitted by steam electric
power plants.
• Water quality, wildlife, and non-cancer and cancer human health impacts from exposure to pollutants
in immediate receiving waters of steam electric power plants.
• Human health impacts - neurological- and cancer-related - caused by exposure to lead, mercury, and
arsenic from consuming fish caught in downstream reaches of receiving waters of steam electric
power plants.
• Exposure to total trihalomethanes (TTHM) in drinking water sources from drinking water systems that
intake water from receiving waters of steam electric power plants, and the resulting impacts on
incidence of bladder cancer cases and bladder cancer deaths.
• Health impacts from cumulative exposures to pollutants discharged by steam electric power plants
through consumption offish caught in immediate receiving waters of steam electric power plants.
• An analysis that evaluates the distribution of costs and benefits among potentially affected
communities (Section 10).
Overall, EPA's EJ analysis showed that the extent to which the technologies steam electric power plants
implement to control wastewater discharges will reduce differential baseline exposures for low-income
and minority populations in affected communities to pollutants in wastewater and resulting human
impacts varies. In particular, benefits associated with improvements to water quality, wildlife, and human
health resulting from reductions in pollutants in surface water and drinking water will accrue to minority
and low-income populations at a higher rate under some or all of the proposed regulatory options, with
Options 3 and 4 generating the greatest improvements. Remaining exposures, impacts, costs, and
benefits analyzed either accrue at a higher rate to populations that are not minority or low-income,
accrue proportionately to all populations, or are small enough that EPA could not conclude whether
changes in disproportionate impacts would occur. While the changes in greenhouse gases (GHGs)
attributable to the proposed regulatory options are small compared to worldwide emissions, findings
from peer-reviewed evaluations demonstrate that actions that reduce GHG emissions are also likely to
reduce climate-related impacts on vulnerable communities, including low-income and minority
communities.
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1. Introduction
1.1 Description of the Effluent Limitations Guidelines Program
Underthe authority of the Clean Water Act, the U.S. Environmental Protection Agency (EPA) develops
national wastewater discharge standards that apply to categories of industrial point source wastewater
dischargers, referred to as effluent limitations guidelines and standards (ELGs). Developed for a specific
industry, ELGs are technology-based standards that industrial point sources subject to them are required,
by regulation, to meet. Standards for direct industrial dischargers are implemented through the National
Pollutant Discharge Elimination System permits issued by states and EPA regional offices. Standards for
indirect dischargers are implemented through EPA, state, or local pretreatment programs.
1.2 Steam Electric Power Generating Effluent Guidelines
One of the categories of industrial wastewater dischargers subject to ELGs is the steam electric power
generating point source category. This category covers power plants operating as utilities which includes
steam electric power plants that use nuclear or fossil fuels (e.g., coal, oil, and natural gas) to produce
electricity. The steam electric ELG sets technology-based standards for wastewater discharges from these
steam electric power plants. The steam electric rule was promulgated in 1974 and has been amended in
1977, 1978, 1980, 1982, 2015, and 2020. While EPA is currently revising the ELGs, permitting authorities
are implementing the requirements contained in the 2015 rule and the 2020 rule. For more information
on the 2015 rule and the 2020 rule see https://www.epa.gov/eg/steam-electric-power-generating-
effluent-guidelines.
1.3 Proposed Supplemental Effluent Limitations Guidelines and Standards for
the Steam Electric Power Generating Point Source Category
EPA's proposed rule contains revised technology-based ELGs for the steam electric power generating
point source category for certain wastestreams. EPA proposes changes to, or solicits comment on,
limitations for flue gas desulfurization (FGD) wastewater, bottom ash (BA) transport water, combustion
residual leachate (CRL), and legacy wastewater at existing sources.
As one of the supplements to the proposed rule, EPA has performed an environmental justice (EJ)
analysis. This document presents that analysis.
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2. Definitions and Terminology
EPA defines EJ as the "fair treatment and meaningful involvement of all people regardless of race, color,
national origin, or income with respect to the development, implementation and enforcement of
environmental laws, regulations and policies" (emphasis added) (U.S. EPA, 2022a).
Fair treatment, as defined by EPA, means that "no group of people should bear a disproportionate share
of the negative environmental consequences resulting from industrial, governmental, and commercial
operations or policies." EPA has also defined meaningful involvement based on four key principles:
"people have an opportunity to participate in decisions about activities that may affect their environment
and/or health; the public's contributions can influence the regulatory agency's decision; community
concerns will be considered in the decision-making process; and decision makers will seek out and
facilitate the involvement of those potentially affected" (U.S. EPA, 2022a).
Throughout this document the terms potential EJ concern (PEJC) and population group(s) of concern are
used:
• A PEJC is defined as "the actual or potential lack of fair treatment or meaningful involvement of
minority populations, low-income populations, tribes, and indigenous peoples in the development,
implementation, and enforcement of environmental laws, regulations, and policies" (U.S. EPA, 2016,
p. 4). In a regulatory context, the term refers to "disproportionate impacts on minority populations,
low-income populations, and/or indigenous peoples that may exist prior to or may be created by the
proposed regulatory action" (U.S. EPA, 2016, p. 4). Therefore, this report uses the term when
discussing whether the results of EPA's quantitative and qualitative analyses indicate that there are
disproportionate impacts under the baseline and/or regulatory options.
• EPA defines population groups of concern as minority populations,2 low-income populations, and
indigenous peoples. Populations who primarily consume fish and/or wildlife for subsistence are also
included as a group that can overlap with other population groups of concern through unique
exposure pathways to pollutants (E.O. 12898, 59 CFR 7629, February 16, 1994). EPA has also advised
that, when appropriate, additional population characteristics-such as life stage and gender-can be
used to evaluate differences within a population group of concern (U.S. EPA, 2016). The term is used
in this report when referring to the apportionment of impacts among minority, low-income, or
indigenous populations as well as individual racial/ethnic population groups (e.g., Hispanic
populations).
In relation to Executive Order (E.O.) 12898, the White House's Council on Environmental Quality defines
minorities as "individual(s) who are members of the following population groups: American Indian or Alaska
Native; Asian or Pacific Islander; Black, not of Hispanic origin; or Hispanic" (U.S. EPA, 2016, p. 6).
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3. Executive Orders
This analysis follows guidance on EJ issued to federal agencies through several Executive Orders (E.O.s).
E.O. 12898 (59 FR 7629, February 16, 1994) sets federal executive policy on EJ. It directs federal agencies,
to the greatest extent practicable and permitted by law, to make achieving EJ part of their mission by
identifying and addressing, as appropriate, disproportionately high and adverse human health or
environmental effects of their programs, policies, and activities on minority populations and low-income
populations in the United States (59 FR 7629, February 16, 1994).
E.O. 13985 (86 FR 7009, January 20, 2021) focuses on creating a "comprehensive approach to advancing
equity for all, including people of color and others who have been historically underserved, marginalized,
and adversely affected by persistent poverty and inequality" (p. 7009). It also calls on agencies to
"recognize and work to redress inequities in their policies and programs that serve as barriers to equal
opportunity"(86 FR 7009, January 20, 2021, p. 7009).
E.O. 14008 (86 FR 7619, February 1, 2021) calls on federal agencies to make achieving EJ part of their
missions "by developing programs, policies, and activities to address the disproportionately high and
adverse human health, environmental, climate-related and other cumulative impacts on disadvantaged
communities, as well as the accompanying economic challenges of such impacts" (p. 7629). It also
declares a policy "to secure environmental justice and spur economic opportunity for disadvantaged
communities that have been historically marginalized and overburdened by pollution and under-
investment in housing, transportation, water and wastewater infrastructure and health care" (86 FR
7619, February 1, 2021, p. 7629).
E.O. 12866 (58 FR 51735, October 4, 1993) instructs federal agencies that, when choosing among
alternative regulatory options in relation to their preferred regulatory options, they should choose
options "that maximize net benefits (including potential economic, environmental, public health and
safety, and other advantages; distributive impacts; and equity), unless a statute requires another
regulatory approach" (p. 1). Additionally, the E.O. states that when an agency determines that a
regulation is the best available option for achieving the regulatory objective, it should design the
regulation in the most cost-effective manner, considering (among several other factors) distributive
impacts and equity (58 FR 51735, October 4, 1993).
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4. Purpose and Outline of the Environmental Justice Analysis
EPA conducted this analysis to provide a robust assessment of the distribution of pollutant exposures,
environmental and human health impacts, and costs and benefits among all populations expected to be
affected by the proposed rule.
To advance the objectives of E.O. 12898, the analysis evaluates the distribution of environmental and
human health impacts under the baseline and regulatory options evaluated, giving particular attention to
whether disproportionately high and adverse impacts are experienced by population groups of concern
under the baseline and whether the regulatory options evaluated mitigate, exacerbate, or create
disproportionately high and adverse impacts among population groups of concern. This analysis also
advances the objectives of E.O. 14008 by evaluating, both quantitatively and qualitatively, some of the
cumulative risks experienced by populations expected to be affected by the proposed rule. The
distribution of these cumulative risks among population groups of concern is assessed underthe baseline
and regulatory options evaluated to determine whether the options mitigate, exacerbate, or create a
disproportionately high distribution of cumulative risks among population groups of concern.
Additionally, this analysis advances the objectives of E.O. 12866, as the costs and benefits of the options
are screened, with the highest magnitude costs and benefits evaluated to provide an assessment of the
distribution of economic impacts among populations expected to be affected by the proposed rule.
Lastly, the analysis advances the objectives of E.O. 13985 by developing a more comprehensive approach
to considering the equity of impacts of the proposed rule, using results from quantitative analyses to
evaluate the distribution of environmental and human health impacts as well as results from qualitative
information gathered through the meaningful involvement of affected populations through public
meetings in several affected communities.
The results of this EJ analysis are presented in the following sections of this document:
• Section 5 presents a review of existing literature on potential EJ concerns related to pollution from
coal-fired power plants.
• Section 6 presents the results of the nationwide proximity analysis EPA performed as an initial
assessment of socioeconomic characteristics of communities living near steam electric power plants
and exposure pathways for pollutants discharged from the plants.
• Section 7 presents the methodology EPA used to evaluate the environmental and socioeconomic
characteristics of communities expected to be affected by the proposed rule and to identify whether
communities had PEJC. This section also presents the methodology EPA used to identify a subset of
communities identified as having PEJC to prioritize for initial outreach to solicit input from community
members. Finally, this section discusses EPA's initial outreach, including planning public meetings and
the results of these meetings.
• Section 8 defines the baseline scenario and each of the regulatory options evaluated in the analysis.
• Section 9 presents the results of the evaluation of the distribution of environmental and/or human
health impacts among populations expected to be affected by the proposed rule under the baseline
and the regulatory options. The results are shown for each of the pollutant exposure pathways
evaluated for the proposed rule-air, surface water, and drinking water. This section also presents the
results of the distribution of cumulative risks among populations expected to be affected by the
proposed rule.
• Section 10 discusses the distribution of benefits and costs of the proposed rule among populations
expected to be affected.
• Section 11 discusses the limitations and uncertainties of the EJ analysis.
• Section 12 discusses the conclusions of the EJ analysis.
4
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5. Literature on Potential Environmental Justice Concerns
Associated with Coal-Fired Power Plants
EPA conducted a literature review to identify academic research and articles on EJ concerns related to
coal-fired power plants. EPA identified 10 papers that focused on coal-fired power plants and EJ issues,
four of which focused on coal-fired power plants in the United States and were considered by the Agency
to be directly relevant to the proposed rule. Three of the four papers focused on a large study on coal-
fired power plants conducted by the National Association for the Advancement of Colored People
(NAACP); the fourth was a study conducted in a coal-producing region evaluating predictors of proximity
to older coal waste impoundments. The findings of the literature review are discussed below.
In 2012, the NAACP published a study evaluating 378 coal-fired power plants in the United States based
on their EJ performance. A plant's EJ performance was determined using a scoring system based on five
factors: emissions of sulfur dioxide (S02), emissions of nitrogen oxides (NOx), size of the population living
within three miles of the plant, median income of the total population living within three miles of the
plant, and the percentage of people of color living within three miles of the plant (NAACP, 2012). The
results of the study's proximity analysis showed that individuals living within three miles of a coal-fired
power plant are on average poorer and more likely to be people of color (NAACP, 2012). Particularly,
coal-fired power plants sited in urban areas are disproportionately located in communities of color
(NAACP, 2012). Focusing on 75 plants that received "failing" EJ performance scores, the study found that
the four million people living within three miles of these plants had an average per capita income of
$17,500, or about $22,600 in 2022 dollars-about 25 percent less than the national average3-and 53
percent were people of color compared to a national average of 36 percent. (NAACP, 2012). While not
included in the report, a follow-on article reported that 78 percent of African Americans in the United
States live within 30 miles of coal-fired power plants (Toomey, 2013). Latino, indigenous, and low-income
communities are on average also more likely to live near coal-fired power plants than the general
population (Toomey, 2013). These findings suggest that coal-fired power plants tend to be located in
poor, minority, and indigenous communities.
Living near coal-fired power plants can be associated with adverse health impacts. These plants produce
air pollutants like S02, NOx, and fine particulate matter (PM2.5). Exposures to S02 and NOx are associated in
the short-term with acute respiratory illnesses like coughing and wheezing, and in the long-term are
associated with asthma (NAACP, 2012). Asthma has been found to particularly affect African Americans,
who are three times more likely, on average, to be hospitalized for asthma than Whites and have a death
rate from asthma that is 172 percent higher than for Whites (NAACP, 2012). Additionally, exposure to
PM2.5 can cause chronic bronchitis, irregular heart conditions, and asthma, and lead to premature death
among people with heart or lung disease (NAACP, 2012). Coal-fired power plants also release heavy
metals like mercury, uranium, arsenic, and lead into the air and water. Pregnant women and their
children are particularly vulnerable to adverse health impacts from exposure to heavy metals, as in vitro
exposures can cause developmental disorders in children like impaired brain function, blindness, and
development delays in general (NAACP, 2012). Indigenous populations can also experience
disproportionate adverse health impacts from exposure to heavy metals, particularly mercury, due to
their higher rates offish consumption (Israel, 2012). These findings suggest that minorities, indigenous
populations, and children potentially face disproportionately high and adverse health impacts from
exposures to pollutants released by coal-fired power plants into the air and water.
The report also found that coal-fired power plants contribute to climate justice issues through emissions
of carbon dioxide (C02) which contribute to climate change (NAACP, 2012). The report cited a statement
made by EPA in 2009 that listed some of the impacts of climate change, including "increased drought,
increased number of heavy downpours and flooding, more frequent and intense heat waves and
3' Expressed in 2022 dollars, the average per capita income in the U.S. was about $28,300.
5
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Section 5—Literature on Potential Environmental Justice Concerns Associated with Coal-Fired Power Plants
wildfires, greater sea level rise, more intense storms, and harm to water resources, agriculture, wildlife,
and ecosystems" (NAACP, 2012, p. 18). The report noted that certain populations-including low-income,
indigenous, minority, elderly, and disabled populations-may face a disproportionate risk from these
climate change impacts, given that they generally have less capacity to recover from such events (NAACP,
2012). Based on these findings, coal-fired power plants may lead to disproportionate risks among these
population groups beyond those who live near a plant by increasing the likelihood of extreme weather
and natural disasters in their communities.
While not addressed by the proposed rule, PEJC have also been studied in coal-producing areas. Since the
decline in the coal industry and in the aftermath of the Martin County, Kentucky coal waste
impoundment disaster, Lievanos et al. (2018) found that the strongest predictors of proximity to older
coal waste impoundments were proximity to abandoned and sealed mines and poverty levels. Particularly
with poverty, the study found that a one percent increase in the percent of block group residents living
below the poverty line is associated with a 52-meter decrease in distance to the nearest coal waste
impoundment sited from 2001 to 2006 (Lievanos et al., 2018). Based on this finding, they concluded that
"block group poverty levels consistently represented the path of least resistance to new hazardous coal
waste impoundments sited" within that period (Lievanos et al., 2018, p. 51). This suggests PEJC among
low-income populations in coal-producing areas with respect to the siting of new coal waste
impoundments and potential increased risks of disproportionate adverse impacts as impoundments age
and become more susceptible to failure.
6
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6. Nationwide Proximity Analysis
As an initial screening of communities potentially affected by the proposed rule, EPA conducted a
nationwide proximity analysis to summarize the socioeconomic characteristics of households living near
steam electric power plants, downstream surface waters affected by plant discharges, and drinking water
systems potentially affected by plant discharges. This gave EPA an initial assessment of whether
communities near steam electric power plants and other sources of exposure to pollutants from the
plants were disproportionately composed of population groups of concern relative to national and state
averages.
6.1 Socioeconomic Characteristics of Populations Residing in Proximity to
Steam Electric Power Plants
For this analysis, EPA assessed the socioeconomic characteristics of the populations within specified
distances of steam electric power plants and of reaches affected by steam electric plant discharges. EPA
conducted this analysis for the set of 92 steam electric power plants for which the Agency modeled non-
zero pollutant loadings under the baseline or regulatory options.
EPA collected 2015 to 2019 population-specific American Community Survey (ACS) data from the U.S.
Census Bureau(2022a) on:
• The percent of the population below the poverty threshold,4 referred to as "low-income population"
in this analysis.
• The percent of the population categorized in various racial/ethnic minority groups.5
EPA compiled these data for Census block groups (CBGs) located within one mile and three miles of
steam electric power plants. EPA assessed the spatial distribution of low-income individuals and specific
race and ethnicity categories subsumed under the term, "minority group" to determine whether people
in these groups are more or less represented in the populations living near steam electric power plants
that discharge BA transport water, FGD wastewater, or CRL compared to the respective state and
national averages.6 PEJC may exist in areas where the percent of the population that is low-income
and/or minority is higher than the state or national averages.
The distance buffers from the steam electric power plants and their associated immediate receiving
reaches7 are denoted below as the "analysis region." Populations within the regions included in the
analysis may be affected by steam electric power plant discharges and other environmental impacts in
the immediate vicinity of the plant in the baseline and by environmental improvements resulting from the
4' For the ACS, the Census Bureau determines poverty status by comparing annual income to a set of dollar
values, called poverty thresholds, that vary by family size, number of children, and the age of the householder.
5' The racial/ethnic categories are based on available fish consumption data as well as the breakout of
ethnic/racial populations in Census data, which distinguishes racial groups within Hispanic and non-Hispanic
categories.
6' The minority groups are: African American (non-Hispanic), Asian (non-Hispanic), Native Hawaiian or Pacific
Islander (non-Hispanic), American Indian or Alaska Native (non-Hispanic), Other non-Hispanic, and Hispanic or
Latino.
7' In this analysis, EPA used the coordinates of each steam electric plant as the basis to define analysis regions
using various distance buffers.
7
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Section 6—Nationwide Proximity Analysis
regulatory options.8 EPA notes that these are not the only populations that could be affected by steam
electric power plants and other environmental impacts. For example, air pollutants emitted by steam
electric power plants may affect populations within hundreds of miles of that plant.
EPA used the U.S. Census Bureau's ACS data for 2015 to 2019 (U.S. Census Bureau, 2022a) to identify
minority and income status at the CBG, analysis region, state, and national levels. Table 1 summarizes the
socioeconomic characteristics of the analysis regions defined using buffer distances of one and three
miles from the steam electric power plants. Table 2 presents this information in terms of the number of
plants with population groups of concern above the national average.
As shown in Table 1, about 50,000 people live within one mile of at least one steam electric power plant
currently discharging BA transport water, FGD wastewater, or CRL to surface waters, and about 600,000
people live within three miles.9 The proportion of populations within all analyzed regions that are
minority (considered as a group, across all racial/ethnic categories) or low-income is smaller than or
similar to the national average; however, the comparison of individual analysis regions around each plant
to national averages shows that varying shares of communities within each distance buffer have low-
income or minority percentages above national averages10. In particular, about one third of the individual
communities have a higher proportion of low-income people and people who identify as Other (non-
Hispanic) than the national average (Table 2).
The simple comparison to the national average may not account for important differences between
states, particularly given the non-uniform geographical distribution of steam electric power plants across
the country. EPA therefore also compared the demographic profile of communities around each plant to
that of the states intersected by each analysis region. Table 3 summarizes the results of this comparison,
while Table 4 summarizes the state statistics against which the communities around each plant were
compared.
Socioeconomic characteristics at the state and national levels are relatively similar (different by fewer
than five individual communities), except for the proportion of people who identify as Native Hawaiian or
Pacific Islander (non-Hispanic), people who identify as American Indian or Alaska Native (non-Hispanic),
and people who identify as Hispanic or Latino. For these characteristics, exceedances of state averages
are greater than exceedances of national averages, especially within the three-mile distance from stream
electric plants (Table 3 and Table 4).
8' The regulatory options are projected to result in reductions (or no change) in pollutant loadings discharged to
receiving waters; therefore, changes are generally anticipated to benefit populations living near the plants.
Throughout this discussion, unless stated otherwise, changes are in the direction of improving environmental
conditions.
For both buffer distances, around 2 percent of CBGs fall within the buffer area around multiple steam electric
plants. As a result, some individuals may be double counted in this estimation of total affected population.
ia A "community" consists of the CBGs within the specified distance of each of the 92 steam electric power plants
discharging BA transport water, FGD wastewater, or CRL to surface waters.
8
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Section 6—Nationwide Proximity Analysis
Table 1. Percent of the Population Living Within 1 and 3 Miles of a Steam Electric Power Plant and Associated Immediate Receiving Reach
Identifying as a Racial or Ethnic Minority or Low-Income, Compared to the General Population
Distance
from Plant
Total
Population
(Millions)3
Percent
Low-
Income
Percent African
American (Non-
Hispanic)
Percent
American
Indian/Alaska
Native
Percent
Asian
Percent Native
Hawaiian/Pacific
Islander
Percent
Other
(Non-
Hispanic)
Percent
Hispanic/Latino
1 mile
0.05
13.1%
7.9%
0.8%
1.2%
0.0%
2.6%
7.0%
3 miles
0.59
12.7%
8.0%
0.7%
1.8%
0.1%
2.5%
6.8%
United States
328.0
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Source: U.S. EPA Analysis, 2023
Notes:
a-For both buffer distances, around two percent of CBGs fall within the buffer area around multiple steam electric plants.
Table 2. Number of Affected Communities Living within 1 and 3 Miles of a Steam Electric Power Plant and Associated Immediate Receiving
Reach That Have a Higher Proportion of Individuals Who Identify as a Racial or Ethnic Minority or Low-Income than the National Average
Number of Communities3 Living in Proximity to Steam Electric Power Plants That Have a Higher Proportion of a/an...
Distance
from Plant
Number
of Plants'5
Low-
Income
Population
African
American (Non-
Hispanic)
Population
Asian
Population
Native
Hawaiian/Pacific
Islander
Population
American
Indian/Alaska
Native
Population
Other (Non-
Hispanic)
Population
Hispanic/Latin
o Population
... than the National Average
1 mile
92
35
16
19
2
4
35
4
3 miles
92
34
19
14
1
9
30
5
United States
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Source: U.S. EPA Analysis, 2023
Notes:
a-ln this analysis, a "community" consists of the CBGs within the specified distance of each of the 92 steam electric power plants discharging BA transport water, FGD wastewater,
or CRL to surface waters. For both buffer distances, around 2 percent of CBGs fall within the buffer area around multiple steam electric plants,
b-lncludes all steam electric plants with non-zero pollutant loadings modeled under the baseline or regulatory options.
9
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Section 6—Nationwide Proximity Analysis
Table 3. Number of Affected Communities Living Within 1 and 3 Miles of a Steam Electric Power Plant and Associated Immediate Receiving
Reach with a Higher Proportion of Individuals Identifying as a Racial or Ethnic Minority or Low-Income than Their State Average
Number of Communities3 Living in Proximity to Steam Electric Power Plants That Have a Higher Proportion of a/an...
Distance
from
Plant
Number
of
Plants
Low-
Income
Population
African
American
(Non-Hispanic)
Population
Asian
Population
Native
Hawaiian/Pacific
Islander
Population
American
Indian/Alaska
Native Population
Other (Non-
Hispanic)
Population
Hispanic/Latino
Population
... than the State Average (b)
1 mile
92
30
15
21
9
5
38
13
3 miles
92
35
13
19
20
18
40
18
Source: U.S. EPA Analysis, 2023.
Notes:
a-ln this analysis, a "community" consists of the CBGs within the specified distance of each of the 92 steam electric power plants discharging BA transport water, FGD wastewater,
or CRLto surface waters. For both buffer distances, around two percent of CBGs fall within the buffer area around multiple steam electric plants.
b-The state average is based on the states intersected by the analysis region around each steam electric power plant. In cases where an analysis region intersects multiple states,
EPA weighted state statistics based on each state's share of the total population within the analysis region.
10
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Section 6—Nationwide Proximity Analysis
Table 4. Socioeconomic Characteristics of the Populations of States with Communities Potentially Affected by
Steam Electric Plant Discharges, Compared to the National Average
Socioeconomic Characteristics of Populations in Service Areas of Affected PWS
State
Percent Below
Poverty Level
Percent African-
American (Non-
Hispanic)
Percent American
Indian/Alaska
Native (Non-
Hispanic)
Percent Asian
(Non-Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent Other
(Non-Hispanic)
Percent
Hispanic/Latino
AL
16.7%
26.5%
0.5%
1.3%
0.0%
1.9%
4.3%
AZ
15.1%
4.2%
3.9%
3.2%
0.2%
2.4%
31.3%
CA
13.4%
5.5%
0.4%
14.3%
0.4%
3.3%
39.0%
DC
16.2%
45.4%
0.2%
3.9%
0.0%
2.8%
11.0%
DE
11.8%
21.7%
0.3%
3.8%
0.0%
2.6%
9.2%
GA
15.1%
31.2%
0.2%
3.9%
0.0%
2.4%
9.5%
IA
11.5%
3.6%
0.3%
2.4%
0.1%
1.9%
6.0%
IL
12.5%
14.0%
0.1%
5.4%
0.0%
2.0%
17.1%
IN
13.4%
9.2%
0.2%
2.3%
0.0%
2.3%
6.9%
KS
12.0%
5.7%
0.7%
2.9%
0.1%
2.9%
11.9%
KY
17.3%
8.0%
0.2%
1.5%
0.1%
2.1%
3.7%
LA
19.2%
32.0%
0.5%
1.7%
0.0%
2.0%
5.1%
MA
10.3%
6.9%
0.1%
6.6%
0.0%
3.0%
11.8%
MD
9.2%
29.4%
0.2%
6.2%
0.0%
3.2%
10.1%
MN
9.7%
6.3%
0.9%
4.8%
0.0%
2.7%
5.4%
MO
13.7%
11.4%
0.4%
2.0%
0.1%
2.5%
4.2%
MS
20.3%
37.6%
0.4%
1.0%
0.0%
1.3%
3.1%
NC
14.7%
21.1%
1.1%
2.8%
0.1%
2.5%
9.4%
ND
10.7%
2.9%
5.1%
1.4%
0.1%
2.3%
3.7%
NE
11.1%
4.7%
0.8%
2.4%
0.1%
2.3%
10.9%
NH
7.6%
1.4%
0.1%
2.7%
0.0%
1.9%
3.7%
NV
13.1%
8.7%
0.9%
8.0%
0.6%
3.8%
28.7%
OH
14.0%
12.2%
0.1%
2.2%
0.0%
2.7%
3.8%
OK
15.7%
7.1%
7.3%
2.1%
0.1%
7.1%
10.6%
PA
12.4%
10.7%
0.1%
3.4%
0.0%
2.1%
7.3%
SC
15.2%
26.6%
0.3%
1.6%
0.1%
2.2%
5.7%
SD
13.1%
2.0%
8.4%
1.4%
0.1%
2.4%
3.8%
TN
15.2%
16.6%
0.2%
1.7%
0.1%
2.1%
5.4%
11
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Section 6—Nationwide Proximity Analysis
Table 4. Socioeconomic Characteristics of the Populations of States with Communities Potentially Affected by
Steam Electric Plant Discharges, Compared to the National Average
Socioeconomic Characteristics of Populations in Service Areas of Affected PWS
State
Percent Below
Poverty Level
Percent African-
American (Non-
Hispanic)
Percent American
Indian/Alaska
Native (Non-
Hispanic)
Percent Asian
(Non-Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent Other
(Non-Hispanic)
Percent
Hispanic/Latino
VA
10.6%
18.8%
0.2%
6.3%
0.1%
3.4%
9.4%
WV
17.6%
3.6%
0.2%
0.8%
0.0%
1.8%
1.6%
United States
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Source: U.S. EPA Analysis, 2023.
12
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Section 6—Nationwide Proximity Analysis
6.2 Socioeconomic Characteristics of Populations Served by Affected Drinking
Water Systems
In addition to steam electric power plants, EPA assessed the socioeconomic characteristics of
communities served by public water systems (PWS) whose source waters are affected by steam electric
power plant discharges. To do this, EPA estimated reductions in pollutant concentrations in PWS source
waters affected by steam electric power plants' discharges, and characterized the populations served by
the PWS directly or indirectly affected by these changes.
As with the proximity analysis for communities near steam electric power plants, EPA began by collecting
2015 to 2019 population-specific ACS data from the U.S. Census Bureau (2022a) on:
• The percent of the population below the poverty threshold,11 referred to as "low-income population"
for this analysis.
• The population categorized in various racial/ethnic minority groups12.
EPA conducted the analysis at the Zip Code Tabulation Area (ZCTA) level13 and compared the
socioeconomic characteristics of the affected ZCTAs (based on the service areas of affected PWS) to those
of the state containing each ZCTA (U.S. Census Bureau, 2022b). PEJC may exist in areas where the percent
of the population that is low-income and/or minority (including specific racial or ethnic categories) is
higher than the respective state average.
Table 5 summarizes the socioeconomic characteristics of the estimated population potentially affected by
changes in drinking water quality resulting from changes in pollutant levels in source waters.
11 For the ACS, the Census Bureau determines poverty status by comparing annual income to a set of dollar
values, called poverty thresholds, that vary by family size, number of children, and the age of the householder.
1Z The racial/ethnic categories are based on available fish consumption data as well as the breakout of
ethnic/racial populations in Census data, which distinguishes racial groups within Hispanic and non-Hispanic
categories. The minority groups are: African American (non-Hispanic), Asian (non-Hispanic), Native Hawaiian or
Pacific Islander (non-Hispanic), American Indian or Alaska Native (non-Hispanic), Other (non-Hispanic), and
Hispanic or Latino.
13, Information on zip codes served for each system was used to approximate a system's service area: EPA
determined ZCTA boundaries to provide a more accurate approximation than boundaries at other geographic
scales {e.g., counties) in the absence of data on actual service areas boundaries for the affected systems. EPA is
now working to collect information on actual service area boundaries for systems that could be used to better
estimate the affected populations. See the 2023 BCA for more information.
13
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Section 6—Nationwide Proximity Analysis
Table 5. Socioeconomic Characteristics of Populations Served by Potentially Affected PWS, Compared to the National Average
Number of
State Potentially
Affected PWS
Population
Served3
Socioeconomic Characteristics of Populations in Service Areas of Affected PWS
Percent
Below
Poverty
Level
Percent
African-
American
(Non-
Hispanic)
Percent
American
Indian/Alask
a Native
(Non-
Hispanic)
Percent
Asian
(Non-
Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent
Other (Non-
Hispanic)
Percent
Hispanic/Latin
o
AL
81
2,008,103
16.6%
23.2%
0.5%
1.4%
0.1%
2.3%
5.7%
AZ
9
14,815
15.9%
2.9%
34.6%
0.8%
0.2%
1.9%
22.1%
CA
96
12,191,421
13.4%
6.4%
0.2%
14.9%
0.3%
2.8%
43.3%
DC
2
632,323
14.3%
39.5%
0.2%
5.4%
0.1%
3.0%
9.9%
DE
1
208,875
11.5%
24.8%
0.2%
5.9%
0.0%
2.7%
13.3%
GA
14
643,252
20.1%
39.3%
0.3%
1.3%
0.0%
2.3%
8.8%
IA
3
159,823
13.4%
7.5%
0.2%
2.8%
0.0%
2.9%
6.5%
IL
31
549,576
14.5%
16.8%
0.2%
1.6%
0.0%
2.4%
6.1%
IN
5
200,792
34.3%
33.5%
0.4%
0.1%
1.0%
4.4%
4.9%
KS
12
168,609
10.9%
7.2%
0.7%
1.3%
0.0%
3.1%
10.5%
KY
38
349,733
18.4%
5.4%
0.1%
0.6%
0.0%
1.9%
4.5%
LA
18
968,256
18.7%
40.0%
0.3%
3.2%
0.0%
2.0%
9.9%
MA
10
358,066
13.3%
3.8%
0.2%
9.5%
0.0%
1.9%
29.0%
MD
19
3,936,765
10.9%
39.0%
0.2%
8.0%
0.1%
3.2%
12.0%
MN
9
667,615
15.4%
15.8%
0.8%
5.4%
0.0%
3.9%
8.3%
MO
19
1,824,039
10.7%
23.0%
0.1%
3.7%
0.0%
2.5%
3.0%
MS
1
1,422
17.4%
2.5%
0.3%
0.0%
0.0%
0.6%
3.8%
NC
37
1,337,529
13.6%
57.9%
0.1%
2.0%
0.0%
2.5%
7.5%
ND
11
33,052
7.6%
1.3%
3.3%
0.7%
0.0%
2.1%
3.2%
NE
9
13,097
8.1%
0.8%
0.1%
0.2%
0.1%
1.2%
2.7%
NH
1
87,932
10.8%
3.0%
0.1%
7.6%
0.0%
2.9%
15.1%
NV
8
2,174,286
14.4%
11.2%
0.4%
9.0%
0.6%
4.0%
32.5%
OH
19
109,283
23.4%
6.1%
0.3%
1.0%
0.0%
2.9%
2.4%
OK
20
33,187
22.2%
1.1%
31.0%
0.8%
0.2%
9.6%
6.3%
PA
68
3,598,707
12.0%
11.9%
0.1%
3.9%
0.0%
2.5%
5.7%
SC
43
473,094
13.0%
22.6%
0.5%
1.5%
0.1%
2.6%
4.8%
SD
98
135,807
14.9%
1.0%
11.1%
1.9%
0.1%
2.1%
3.6%
14
-------
Section 6—Nationwide Proximity Analysis
Table 5. Socioeconomic Characteristics of Populations Served by Potentially Affected PWS, Compared to the National Average
Socioeconomic Characteristics of Populations in Service Areas of Affected PWS
State
Number of
Potentially
Affected PWS
Population
Served3
Percent
Below
Poverty
Level
Percent
African-
American
(Non-
Hispanic)
Percent
American
Indian/Alask
a Native
(Non-
Hispanic)
Percent
Asian
(Non-
Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent
Other (Non-
Hispanic)
Percent
Hispanic/Latin
o
TN
43
2,113,168
12.4%
16.6%
0.2%
2.7%
0.1%
2.6%
7.5%
VA
35
3,090,649
7.5%
15.7%
0.2%
12.4%
0.1%
4.2%
14.5%
WV
21
256,821
19.6%
3.9%
0.1%
2.1%
0.0%
2.9%
2.3%
AL
81
2,008,103
16.6%
23.2%
0.5%
1.4%
0.1%
2.3%
5.7%
AZ
9
14,815
15.9%
2.9%
34.6%
0.8%
0.2%
1.9%
22.1%
CA
96
12,191,421
13.4%
6.4%
0.2%
14.9%
0.3%
2.8%
43.3%
DC
2
632,323
14.3%
39.5%
0.2%
5.4%
0.1%
3.0%
9.9%
DE
1
208,875
11.5%
24.8%
0.2%
5.9%
0.0%
2.7%
13.3%
GA
14
643,252
20.1%
39.3%
0.3%
1.3%
0.0%
2.3%
8.8%
Total
781
38,340,097
United
States
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Source: U.S. EPA Analysis, 2023.
Notes:
a-The affected population is based on the total population served reported by SDWIS for affected PWSs within each state.
15
-------
Section 6—Nationwide Proximity Analysis
As Table 5 shows, more than four million people, across over 2,000 ZCTAs and 36 states, are served by
PWSs potentially affected by the estimated changes in source water quality under the regulatory options.
Most of the 36 states with affected PWS serve ZCTAs with higher proportions of low-income, American
Indian or Alaska Native (non-Hispanic), Native Hawaiian or Pacific Islander (non-Hispanic), Other (non-
Hispanic) populations than the national average. Additionally, 25 percent of states with affected PWSs
serve ZCTAs with higher proportions of Hispanic or Latino populations than the national average.
Table 6 and Table 7 summarize the estimated tribal area population potentially affected by changes in
drinking water quality as a result of steam electric power plant discharges. The analysis compares the
socioeconomic characteristics of the affected tribal areas to the relevant state averages as well as the
national average.
16
-------
Section 6—Nationwide Proximity Analysis
Table 6. Percent of the Population in Tribal Areas with an Affected PWS Identifying as Low-Income
Compared to Their Respective State Average and the National Average
States with Affected
Tribal Areas
Total Population
Percent Low-Income Population
Tribal Area
Affected Population3
Total for Tribal
Area
State(s)
Population
Tribal Area
State Average
Crow Creek Reservation
SD
1,357
2,176
870,638
36.5%
13.1%
Lake Traverse Reservation
ND, SD
230
11,095
1,627,355
21.4%
12.0%
Lower Brule Reservation
SD
2,116(b)(c)
1,689
870,638
38.0%
13.1%
Navajo Nation
AZ, NM, UT
1,190
172,813
5,189,302
38.7%
13.5%
Otoe-Missouria
OK
250
880
3,932,870
15.9%
15.7%
Pine Ridge Reservation
NE, SD
8
19,950
2,785,209
45.3%
11.7%
Rosebud Indian Reservation
SD
9
11,404
870,638
58.7%
13.1%
Standing Rock Reservation
ND, SD
6,839
8,553
1,627,355
41.3%
12.0%
Yankton Reservation
SD
1,064
6,824
870,638
22.9%
13.1%
United States
13.7%
Source: U.S. EPA Analysis, 2023.
Notes:
a-The affected population is based on the population served by the PWS. In some cases, the PWS serves both the tribal area and surrounding service areas.
b-PWS ID 84690026 serves several reservations and counties. EPA distributed the SDWIS-reported population served equally over the three reservations served: Lower Brule Reservation, Pine Ridge
Reservation, and Rosebud Indian Reservation.
c-PWS ID 84690441 serves the Lower Brule Reservation and surrounding South Dakota counties. As a result, the SDWIS-reported population served exceeds the Census-reported total population of
the reservation. The affected percentage of tribal area was adjusted to 80 percent to reflect the fact that the majority of the reservation is likely served by the affected PWS.
17
-------
Section 6—Nationwide Proximity Analysis
Table 7. Percent of Population in Tribal Areas with an Affected PWS Identifying as a Racial or Ethnic Minority
Compared to Their Respective State Average and the National Average
Tribal Area
States
Total Population
Percent African
American
(Non-Hispanic)
Percent
American
Indian/Alaska
Native
Percent Asian
Percent Native
Hawaiian/
Pacific Islander
Percent Other
(Non-Hispanic)
Percent
Hispanic/Latino
Affected
Population3
Tribal
Area
State(s)
Population
Tribal
State
Average
(Avg.)
Tribal
State
Avg.
Tribal
State
Avg.
Tribal
State
Avg.
Tribal
State
Avg.
Tribal
State
Avg.
Crow Creek
Reservation
SD
1,357
2,176
870,638
1.6%
2.0%
85.0%
8.4%
0.0%
1.4%
0.0%
0.1%
1.0%
2.4%
4.6%
3.8%
Lake Traverse
Reservation
ND, SD
230
11,095
1,627,355
0.6%
2.4%
40.2%
6.9%
0.0%
1.4%
0.0%
0.1%
2.4%
2.3%
4.9%
3.8%
Lower Brule
Reservation
SD
2,116b'c
1,689
870,638
0.2%
2.0%
90.6%
8.4%
0.4%
1.4%
0.2%
0.1%
0.9%
2.4%
1.4%
3.8%
Navajo Nation
AZ, NM,
UT
1,190
172,813
5,189,302
0.2%
1.4%
95.2%
4.1%
0.3%
2.0%
0.1%
0.5%
1.0%
2.2%
1.7%
28.1%
Otoe-Missouria
OK
250
880
3,932,870
0.3%
7.1%
32.8%
7.3%
0.5%
2.1%
0.2%
0.1%
14.2%
7.1%
9.8%
10.6%
Pine Ridge
Reservation
NE, SD
8
19,950
2,785,209
0.1%
3.8%
83.7%
3.2%
0.1%
2.1%
0.0%
0.1%
1.8%
2.3%
3.5%
8.7%
Rosebud Indian
Reservation
SD
9
11,404
870,638
0.1%
2.0%
88.1%
8.4%
1.7%
1.4%
0.0%
0.1%
1.4%
2.4%
1.2%
3.8%
Standing Rock
Reservation
ND, SD
6,839
8,553
1,627,355
0.2%
2.4%
74.7%
6.9%
0.0%
1.4%
0.0%
0.1%
1.7%
2.3%
2.6%
3.8%
Yankton
Reservation
SD
1,064
6,824
870,638
0.1%
2.0%
39.4%
8.4%
0.2%
1.4%
0.1%
0.1%
5.6%
2.4%
4.9%
3.8%
United States
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Source: U.S. EPA Analysis, 2023.
Notes:
a-The affected population is based on the population served by the PWS. In some cases, the PWS serves both the tribal area and surrounding service areas.
b-PWS ID 84690026 serves several reservations and counties. EPA distributed the SDWIS-reported population served equally over the three reservations served: Lower Brule Reservation, Pine Ridge
Reservation, and Rosebud Indian Reservation.
c-PWS ID 84690441 serves the Lower Brule Reservation and surrounding South Dakota counties. As a result, the SDWIS-reported population served exceeds the Census-reported total population of
the reservation. The affected percentage of tribal area was adjusted to 80 percent to reflect that the majority of the reservation is likely served by the affected PWS.
18
-------
Section 6—Nationwide Proximity Analysis
As shown in Table 6, affected tribal areas consistently have higher proportions of people who are below
the poverty level compared to both state and national averages. As shown in Table 7, affected tribal areas
have higher proportions of people who belong to some minority racial/ethnic categories other than
American Indian/Alaska Native (non-Hispanic) compared to state and national averages. In particular, the
Otoe-Missouria tribal area has twice the proportion of people who identify as "Other (non-Hispanic)"
than the state average and over five times the national average.
6.3 Socioeconomic Characteristics of Populations Affected by Changes in
Exposure to Pollutants in Downstream Surface Waters
Lastly, EPA evaluated the socioeconomic characteristics of communities within 50 miles14 of reaches of
affected by steam electric plant discharges, including both reaches that receive discharges from steam
electric power plants and downstream reaches.15 To assess the socioeconomic characteristics of these
communities, EPA collected 2015 to 2019 population-specific ACS data (U.S. Census Bureau, 2022a) on:
• The percent of the population below the poverty threshold,16 referred to as "low-income population"
in this analysis.
• The population categorized in various racial/ethnic minority groups.17
EPA compared the socioeconomic characteristics of these areas to national averages. PEJC may exist in
areas where the percent of the population that is low-income and/or minority (including specific racial or
ethnic categories) is higher than the national average.
EPA conducted this analysis for communities affected by changes in pollutant loadings under two periods
(Period l18 and Period 219). Given that the results of the proximity analysis show similar water quality
improvement and distributions in socioeconomic characteristics among affected communities between
Period 1 and Period 2, with only differences in magnitude, results are only presented and discussed for
Period 2 (Table 8-Table 10).20
14 See the 2023 BCA for an explanation of why a 50-mile radius was used to estimate the potentially affected
population.
15, The analysis defines "communities in proximity to reaches" as the aggregate populations residing in CBGs within
50 miles of all reaches within 300 km of steam electric power plant outfalls with nonzero loadings, which
includes approximately 121.1 million people as of 2019. This analysis provides total population and does not
make adjustments for the fraction of this population that consumes self-caught fish.
16, For the ACS, the Census Bureau determines poverty status by comparing annual income to a set of dollar
values, called poverty thresholds, that vary by family size, number of children, and the age of the householder.
"¦ The racial/ethnic categories are based on available fish consumption data as well as the breakout of
ethnic/racial populations in Census data, which distinguishes racial groups within Hispanic and non-Hispanic
categories. The minority groups are: African American (non-Hispanic), Asian (non-Hispanic), Native Hawaiian or
Pacific Islander (non-Hispanic), American Indian or Alaska Native (non-Hispanic), Other (non-Hispanic), and
Hispanic or Latino.
18, Period 1 covers the years 2025 through 2029, when the universe of steam electric power plants would
transition from current (baseline) treatment practices to practices that achieve the revised limitations (2023
BCA).
19, Period 2 covers the years 2030 through 2049: the post-transition period during which the full universe of plants
is projected to employ treatment practices that achieve the revised limitations.
2a Results for Period 1 can be found in Appendix A.
19
-------
Section 6—Nationwide Proximity Analysis
Table 8. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of
Selected Pollutants Under the Regulatory Options Compared to the National Average (Period 2)
Pollutant
Changes in
Number of Downstream Reaches
a
Percent Low-Income Population
Concentrations
Option 1
Option 2
Option 3
Option 4
Option 1
Option 2
Option 3
Option 4
Antimony
Decreases'3
87
3,423
6,885
7,339
6.3%
15.2%
16.1%
16.2%
No changes
9226
5,890
2,428
1,974
16.1%
15.8%
14.6%
14.2%
Arsenic
Decreases
7,136
7,869
9,147
9,313
14.8%
15.5%
15.4%
15.6%
No changes
2,177
1,444
166
0
19.5%
16.2%
32.8%
0.0%
Cadmium
Decreases
7,136
7,869
9,147
9,313
14.8%
15.5%
15.4%
15.6%
No changes
2,177
1,444
166
0
19.5%
16.2%
32.8%
0.0%
Cyanide3
Decreases
0
3,336
3,336
4,237
0.0%
16.5%
16.5%
18.3%
No changes
4237
901
901
0
18.3%
26.5%
26.5%
0.0%
Lead3
Decreases
87
3,423
6,885
7,339
6.3%
15.1%
15.9%
16.0%
No changes
7266
3,930
468
14
16.8%
17.2%
18.4%
6.1%
Manganese
Decreases
87
3,423
6,885
7,339
6.3%
15.2%
16.1%
16.2%
No changes
9226
5,890
2,428
1,974
16.1%
15.8%
14.6%
14.2%
Mercury
Decreases
7,136
7,869
9,147
9,313
14.8%
15.5%
15.4%
15.6%
No changes
2,177
1,444
166
0
19.5%
16.2%
32.8%
0.0%
Thallium
Decreases
87
3,423
6,885
7,339
6.3%
15.2%
16.1%
16.2%
No changes
9226
5,890
2,428
1,974
16.1%
15.8%
14.6%
14.2%
United States
13.7%
Source: U.S. EPA Analysis, 2023.
Notes:
a-Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants
(4,237 and 7,353 reaches for cyanide and lead, respectively, compared to 9,313 reaches for other pollutants).
b-Under the regulatory options, the largest change in the concentration of the pollutants analyzed is a decrease in Manganese of 2.4347 mg/L. Given the small range of pollutant changes observed-
zero mg/L to -2.4347 mg/L-, EPA generalized these changes as "decreases" for each pollutant for ease of comprehension.
20
-------
Section 6—Nationwide Proximity Analysis
Table 9. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants Under
the Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 2)
Pollutant
Changes in
Number of Downstream
Reaches3
Percent African American
Percent American Indian/
Alaska Native
Percent Asian
Concentrations
Option
1
Option
2
Option
3
Option
4
Option
1
Option
2
Option
3
Option
4
Option
1
Option
2
Option
3
Option
4
Option
1
Option
2
Option
3
Option
4
Antimony
Decreases111
87
3,423
6,885
7,339
0.1%
0.3%
0.6%
0.6%
6.8%
3.6%
3.8%
3.7%
0.0%
0.0%
0.1%
0.1%
No changes
9226
5,890
2,428
1,974
0.5%
0.6%
0.3%
0.3%
3.5%
3.7%
3.5%
3.6%
0.1%
0.1%
0.1%
0.1%
Arsenic
Decreases
7,136
7,869
9,147
9,313
0.3%
0.3%
0.5%
0.5%
3.7%
3.8%
3.7%
3.7%
0.1%
0.1%
0.1%
0.1%
No changes
2,177
1,444
166
0
1.5%
3.4%
0.2%
0.0%
3.3%
1.8%
1.3%
0.0%
0.1%
0.1%
0.0%
0.0%
Cadmium
Decreases
7,136
7,869
9,147
9,313
0.3%
0.3%
0.5%
0.5%
3.7%
3.8%
3.7%
3.7%
0.1%
0.1%
0.1%
0.1%
No changes
2,177
1,444
166
0
1.5%
3.4%
0.2%
0.0%
3.3%
1.8%
1.3%
0.0%
0.1%
0.1%
0.0%
0.0%
Cyanide3
Decreases
0
3,336
3,336
4,237
0.0%
0.3%
0.3%
0.3%
0.0%
3.2%
3.2%
3.0%
0.0%
0.0%
0.0%
0.0%
No changes
4,237
901
901
0
0.3%
0.3%
0.3%
0.0%
3.0%
2.3%
2.3%
0.0%
0.0%
0.0%
0.0%
0.0%
Lead3
Decreases
87
3,423
6,885
7,339
0.1%
0.3%
0.6%
0.5%
6.8%
3.8%
3.9%
3.8%
0.0%
0.0%
0.1%
0.1%
No changes
7,266
3,930
468
14
0.6%
0.9%
0.2%
0.5%
3.5%
3.8%
2.0%
2.9%
0.1%
0.1%
0.1%
0.1%
Manganese
Decreases
87
3,423
6,885
7,339
0.1%
0.3%
0.6%
0.6%
6.8%
3.6%
3.8%
3.7%
0.0%
0.0%
0.1%
0.1%
No changes
9,226
5,890
2,428
1,974
0.5%
0.6%
0.3%
0.3%
3.5%
3.7%
3.5%
3.6%
0.1%
0.1%
0.1%
0.1%
Mercury
Decreases
7,136
7,869
9,147
9,313
0.3%
0.3%
0.5%
0.5%
3.7%
3.8%
3.7%
3.7%
0.1%
0.1%
0.1%
0.1%
No changes
2,177
1,444
166
0
1.5%
3.4%
0.2%
0.0%
3.3%
1.8%
1.3%
0.0%
0.1%
0.1%
0.0%
0.0%
Thallium
Decreases
87
3,423
6,885
7,339
0.1%
0.3%
0.6%
0.6%
6.8%
3.6%
3.8%
3.7%
0.0%
0.0%
0.1%
0.1%
No changes
9,226
5,890
2,428
1,974
0.5%
0.6%
0.3%
0.3%
3.5%
3.7%
3.5%
3.6%
0.1%
0.1%
0.1%
0.1%
United States
12.2%
0.7%
5.4%
Source: U.S. EPA Analysis, 2023.
Notes:
a-Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants
(4,237 and 7,353 reaches for cyanide and lead, respectively, compared to 9,313 reaches for other pollutants).
b-Under the regulatory options, the largest change in the concentration of the pollutants analyzed is a decrease in Manganese of 2.4347 mg/L. Given the small range of pollutant changes observed-
zero mg/L to -2.4347 mg/L-, EPA generalized these changes as "decreases" for each pollutant for ease of comprehension.
21
-------
Section 6—Nationwide Proximity Analysis
Table 10. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants Under the
Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 2)
Pollutant
Changes in
Number of Downstream
Reaches3
Percent Native Hawaiian/
Pacific Islander
Percent Other (Non-Hispanic)
Percent Hispanic/Lati
no
Concentrations
Option
1
Option
2
Option
3
Option
4
Option
1
Option
2
Option
3
Option
4
Option
1
Option
2
Option
3
Option
4
Option
1
Option
2
Option
3
Option
4
Antimony
Decreases111
87
3,423
6,885
7,339
2.7%
2.3%
2.5%
2.5%
10.2%
12.1%
10.6%
10.4%
9.3%
13.6%
13.2%
13.2%
No changes
9,226
5,890
2,428
1,974
2.5%
2.6%
2.4%
2.4%
10.6%
9.6%
10.4%
10.8%
13.5%
13.1%
13.6%
13.5%
Arsenic
Decreases
7,136
7,869
9,147
9,313
2.5%
2.4%
2.5%
2.5%
9.3%
10.8%
10.6%
10.5%
13.0%
13.1%
13.3%
13.3%
No changes
2,177
1,444
166
0
2.6%
3.2%
1.5%
0.0%
17.2%
7.1%
3.6%
0.0%
15.0%
16.1%
16.8%
0.0%
Cadmium
Decreases
7,136
7,869
9,147
9,313
2.5%
2.4%
2.5%
2.5%
9.3%
10.8%
10.6%
10.5%
13.0%
13.1%
13.3%
13.3%
No changes
2,177
1,444
166
0
2.6%
3.2%
1.5%
0.0%
17.2%
7.1%
3.6%
0.0%
15.0%
16.1%
16.8%
0.0%
Cyanide3
Decreases
0
3,336
3,336
4,237
0.0%
2.2%
2.2%
2.2%
0.0%
12.8%
12.8%
11.8%
0.0%
14.4%
14.4%
14.5%
No changes
4,237
901
901
0
2.2%
2.3%
2.3%
0.0%
11.8%
7.2%
7.2%
0.0%
14.5%
15.1%
15.1%
0.0%
Lead3
Decreases
87
3,423
6,885
7,339
2.7%
2.3%
2.5%
2.5%
10.2%
13.0%
11.2%
10.9%
9.3%
13.6%
13.2%
13.2%
No changes
7,266
3,930
468
14
2.5%
2.8%
2.2%
2.6%
11.0%
8.0%
5.9%
10.1%
13.5%
12.6%
14.2%
10.9%
Manganese
Decreases
87
3,423
6,885
7,339
2.7%
2.3%
2.5%
2.5%
10.2%
12.1%
10.6%
10.4%
9.3%
13.6%
13.2%
13.2%
No changes
9,226
5,890
2,428
1,974
2.5%
2.6%
2.4%
2.4%
10.6%
9.6%
10.4%
10.8%
13.5%
13.1%
13.6%
13.5%
Mercury
Decreases
7,136
7,869
9,147
9,313
2.5%
2.4%
2.5%
2.5%
9.3%
10.8%
10.6%
10.5%
13.0%
13.1%
13.3%
13.3%
No changes
2,177
1,444
166
0
2.6%
3.2%
1.5%
0.0%
17.2%
7.1%
3.6%
0.0%
15.0%
16.1%
16.8%
0.0%
Thallium
Decreases
87
3,423
6,885
7,339
2.7%
2.3%
2.5%
2.5%
10.2%
12.1%
10.6%
10.4%
9.3%
13.6%
13.2%
13.2%
No changes
9,226
5,890
2,428
1,974
2.5%
2.6%
2.4%
2.4%
10.6%
9.6%
10.4%
10.8%
13.5%
13.1%
13.6%
13.5%
United States
0.2%
2.7%
18.8%
Source: U.S. EPA Analysis, 2023.
Notes:
a-Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants
(4,237 and 7,353 reaches for cyanide and lead, respectively, compared to 9,313 reaches for other pollutants).
b-Under the regulatory options, the largest change in the concentration of the pollutants analyzed is a decrease in Manganese of 2.4347 mg/L. Given the small range of pollutant changes observed-
zero mg/L to -2.4347 mg/L-, EPA generalized these changes as "decreases" for each pollutant for ease of comprehension.
22
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Section 6—Nationwide Proximity Analysis
As shown in Table 8, communities living near the majority of reaches (regardless of the associated water
quality change under the regulatory options) have a larger proportion of low-income population than the
national average. As shown in Table 9 and Table 10, all of the reaches (regardless of the associated water
quality change under the regulatory options) have:
• A smaller proportion of people who identify as Black or African American (non-Hispanic), people who
identify as Asian (non-Hispanic), and people who identify as Hispanic or Latino than national averages.
• A larger proportion of people who identify as American Indian or Alaska Native (non-Hispanic), people
who identify as Native Hawaiian or Pacific Islander (non-Hispanic), and people who identify as Other
(non-Hispanic) than national averages.
6.4 Key Conclusions
The results of EPA's power plant proximity analysis indicates that, similar to the findings of the literature
review, steam electric power plants are disproportionately located in low-income or minority
communities. The analysis shows that communities located within one and three miles of a steam electric
power plant have larger proportions of population groups of concern (American Indian or Alaska Native
[non-Hispanic], Native Hawaiian or Pacific Islander [non-Hispanic], and Hispanic or Latino) than the
average community when compared to state averages. Accounting for the differences when comparing
to the national average, EPA concludes that while communities living in proximity to steam electric power
plants may have smaller total populations on average, they tend to have larger proportions of population
groups of concern.
Additionally, the PWS and downstream proximity analyses indicate that, like the literature review
suggests, population groups of concern may experience disproportionate impacts from pollutants
discharged by steam electric power plants. The PWS analysis shows that populations served by potentially
affected PWSs have larger proportions of population groups of concern (American Indian or Alaska Native
[non-Hispanic], Native Hawaiian or Pacific Islander [non-Hispanic], Other [non-Hispanic], and Hispanic or
Latino) than the average community in the United States. Focusing on PWSs serving tribal areas, PWSs
were found to serve areas with larger proportions of population groups of concern (low-income and racial
and ethnic minorities other than American Indian or Alaska Native [non-Hispanic]) than the average
community in the United States. Furthermore, the downstream analysis shows that the majority of
downstream reaches of receiving waters of steam electric power plants have communities living within
50 miles with larger proportions of population groups of concern (low-income, American Indian or Alaska
Native [non-Hispanic], Native Hawaiian or Pacific Islander [non-Hispanic], and Other [non-Hispanic]) than
the average community in the United States.
23
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7. Engagement with Communities with Potential
Environmental Justice Concerns
As part of the EJ analysis, EPA conducted initial outreach with a subset of affected communities identified
as having PEJC due to their socioeconomic and environmental characteristics. In some communities, this
outreach led to public meetings. The purpose of the meetings was to begin communicating with local
communities, inform communities of the proposed regulatory action, and get their input on their
preferences for regulatory requirements for steam electric power plants. Additionally, EPA used the
public meetings to collect information on environmental and socioeconomic impacts and concerns in
communities to improve its analyses of distributional impacts of the proposed rule.
This section discusses, the process by which EPA identified and chose communities with PEJC for initial
outreach, the approach the Agency used to plan the meetings, and the input received at the meetings.
7.1 Evaluating PEJC in Communities Affected by the Proposed Rule
EPA performed a set of screening analyses to identify the environmental and socioeconomic
characteristics of all the communities that are expected to be affected via relevant exposure pathways by
steam electric power plants within the scope of the proposed rule. For these analyses, steam electric
power plants were considered in-scope if they were identified as having a retirement date after 2023
(including those with no announced retirement date) and costs for FGD wastewater, BA transport water,
and/or CRL. The exposure pathways analyzed in the screening analyses were air, surface water, and
drinking water. EPA used the Office of Water's EJSCREENBatch tool for the screening analyses (U.S. EPA,
2022b). The tool was chosen because it can perform batch screening analyses for multiple locations at
once, improving the efficiency of the nationwide screening analysis. It also enables users to perform
screening analyses around surface waters and other features that cannot be directly accommodated by
EPA's Environmental Justice Screening and Mapping Tool (EJScreen) itself (U.S. EPA, 2019a).
EPA's specific approach in using EJSCREENBatch for each exposure pathway is discussed below.
7.1.1 Air Screening Analysis
EPA selected one- and three-mile buffers around the facility GIS coordinates as the appropriate distance
for screening the air pathway. These distances were chosen to be consistent with the buffer distances the
Office of Air and Radiation uses when performing screening analyses for communities surrounding
industrial sources that are expected to be exposed to air emissions (U.S. EPA, 2021a). These are the
distances at which air pollution concentrations will be highest before the plume disperses. For each
steam electric power plant, EPA used the EJSCREENBatch tool to draw one- and three-mile buffers,
generating aggregate raw values and state and national percentile values at each buffer distance for
relevant demographic and environmental indicators. Automatically generated correlation plots and box
plots with the state and national percentile results at each buffer distance are presented in Appendix B,
Section 1, to facilitate visualization of these data.
7.1.2 Downstream Surface Water Screening Analysis
EPA chose buffer distances of one-, three-, 50-, and 100-miles around the downstream waterbody
segment, defined as 300 kilometers (about 187 miles) downstream of the initial common identifiers
(COMIDs) identified for each effluent discharge (USGS, 2022; U.S. EPA, 2022c). The downstream distance
of 300 kilometers was chosen to correspond with the downstream distance used in the Downstream Fate
and Transport Equations (D-FATE) model. This model is used to estimate the concentrations of pollutants
in downstream reaches of receiving waters of steam electric power plants and serves as an input to the
risk assessment of relevant health endpoints. The 50- and 100-mile buffers were used to account for
potential exposures among individuals traveling to the waterbodies to recreate or engage in other
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
activities; the one- and three-mile buffers were used based on recommended buffer distances for
screening analyses (U.S. EPA, 2019a). Aggregate raw values and state and national percentile values for
the demographic and environmental indicators were then retrieved for each COMID within the defined
areas. Automatically generated correlation plots and box plots with the state and national percentile
results at each buffer distance are presented in Appendix B, Section 2, to facilitate visualization of these
data.
7.1.3 Drinking Water Screening Analysis
EPA selected public water system IDs (PWSIDs) for drinking water systems intaking water from receiving
waters of in-scope steam electric power plants, associated zip codes from EPA's Fourth Unregulated
Contaminant Monitoring Rule (UCMR4) and Safe Drinking Water Information System (SDWIS) datasets,
and 2019 ZCTAs from the U.S. Census Bureau's TIGER/Line shapefiles (U.S. EPA, 2021b; U.S. EPA, 2022d;
U.S. Census Bureau, 2022b). Zip code information from UCMR4 and SDWIS was used to estimate the
service area boundaries for each of the PWSIDs in the absence of a complete dataset of actual service
area boundaries for all PWS.21
Before the analysis was run in the EJSCREENBatch tool, EPA used ArcGIS to merge the dataset of the
PWSIDs and associated zip codes served with the shapefile dataset of the 2019 ZCTAs.22 This created one
dataset in which the zip code(s) served for each system were listed along with the zip code boundaries.
For those systems with multiple zip codes served, EPA used ArcGIS to dissolve the boundaries of the
individual zip codes into one large boundary. This simplified the analysis: when the dataset was run
through the tool, for the systems with multiple zip codes served, the tool generated aggregate indicator
results for one area rather than several small areas.
The screening analysis was performed using the EJSCREENBatch tool to draw the service area polygons
with a buffer distance of 0.01 miles, as the tool does not allow users to set a buffer distance of zero miles
This, in effect, draws the service area polygon 0.01 miles outside the actual ZCTA-estimated service area.
Automatically generated correlation plots and box plots with the state and national percentile results at
each buffer distance are presented in Appendix B, Section 3, to facilitate visualization of these data.
7.2 Identifying Communities with PEJC
After completing the screening analyses, EPA used the results23 to inform the selection of a subset of
communities with PEJC that would be prioritized for initial outreach and engagement. EPA defined a
community as having PEJC if its indicator results met one or more of the following indicator criteria:
2L The UCMR4 dataset was the primary source used for identifying zip code(s) served for each PWSID. The UCMR4
collected information from all large systems and a random sample of 800 small systems on the zip code(s) those
systems served. For systems EPA identified that were not found in the UCMR4 dataset, the zip code reported
for the system in the SDWIS dataset was used as the zip code served for that system. The zip codes reported in
the SDWIS dataset represent the zip codes associated with the location of the system, which may not in all
cases accurately represent the zip code(s) served by the system. Understanding this, EPA determined this
method to be appropriate in the absence of data on the zip code(s) served for every system.
2Z Additionally, the 2019 ZCTAs dataset was used to generate spatial boundaries for the zip code(s) served by each
system. The zip code boundaries included in the 2019 ZCTAs dataset are approximate area representations of
U.S. Postal Service (USPS) zip codes, so there is some error in the populations included under respective zip
codes. Additionally, the U.S. Census Bureau cannot estimate ZCTAs for all USPS zip codes, so EPA could not
analyze some systems as there were no ZCTA boundaries estimated for the zip code(s) they served.
Understanding these limitations, EPA determined the 2019 ZCTAs dataset was an appropriate dataset to use for
the analysis given the absence of a comprehensive zip code boundary dataset.
23- U.S. EPA, 2022b.
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
• Both demographic (minority and low-income) indicators and at least one environmental indicator
above the 50th percentile nationally or all environmental indicators and at least one demographic
indicator above the 50th percentile nationally.
• Two or more demographic and/or environmental indicators above the 80th percentile nationally.
• One or more demographic and/or environmental indicators above the 90th percentile nationally.
• One or more demographic and/or environmental indicators above the 95th percentile nationally.
Communities with indicator results that did not meet any of the indicator criteria were considered less
likely to have PEJC and were not included in the tiering for initial community outreach and engagement.
To avoid any bias that a single criterion might contain, EPA retained the communities that met one or
more of the indicator criteria. However, to prioritize initial outreach and engagement, EPA then sorted
these communities into tiers based on the number of indicators exceeded:
• Tier 1: A community's indicator results meet all four indicator criteria.
• Tier 2: A community's indicator results meet two or three indicator criteria.
• Tier 3: A community's indicator results meet one indicator criteria.
EPA considered communities sorted under Tier 1 to be the highest-priority communities for initial
outreach and engagement.
In addition to the indicator criteria, EPA verified its results in two ways. First, EPA analyzed the aggregate
raw indicator values and other outputs generated by the EJSCREENBatch tool to verify that communities
with PEJC were not being omitted. Second, EPA looked at the top 10 power plants, downstream receiving
waters, and PWSs with the most indicators over the 80th percentile nationally for each screening analysis.
Comparing these results to those from EPA's indicator criteria approach shows that approach captured all
top 10 facilities.
7.3 Choosing Communities for Initial Outreach
Because EPA could only meet with a subset of communities with PEJC during the proposal phase of the
rulemaking process, the Agency prioritized meeting with communities that may be more likely to have
PEJC.
EPA generated lists of Tier 1, Tier 2, and Tier 3 communities, 10 each, for a total of 30. Each list of
communities was about evenly split between communities potentially affected by power plants,
downstream surface waters, and drinking water systems, with three plants, four downstream surface
waters (two from the one- and three-mile buffer screening and two from the 50- and 100-mile buffer
screening), and three drinking water systems.
In choosing the subset of locations, EPA considered tiering results at every buffer distance. For the air
screening analysis, there were no substantial differences in indicator criteria and tiering results for steam
electric power plants between the one-mile and three-mile buffer distances used. Therefore, the subsets
of steam electric power plants that EPA chose for each list were representative of areas with PEJC at both
buffer distances. For the downstream surface water screening analysis, there were no substantial
differences in indicator criteria and tiering results for surface waters between the one-mile and three-
mile buffer distances, but there were substantial differences between the one- and three-mile results and
the 50- and 100-mile results. Because of this, EPA accounted for both sets of results in its tier lists. For the
drinking water screening analysis, this consideration was not relevant as only one buffer distance-0.01
miles-was used. EPA also considered geographic diversity, including various states and regions to ensure
that community input would reflect nationwide variation in impacts and concerns among communities
with PEJC.
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
EPA conducted initial outreach with nine communities. The Agency's first choice was the top three Tier 1
communities from each of the three screening analyses. For the surface water and drinking water
screening analyses, though there were no Tier 1 communities were in scope. EPA instead chose the top
Tier 2 communities or Tier 3 communities which EPA had engaged with prior to the decision to conduct
the current rulemaking.
7.3.1 Communities Chosen for Initial Outreach
The final list of communities chosen for initial outreach is presented in Table 11. Communities that EPA
engaged with prior to the initiation of the current rule are indicated by a "Yes" in the "Pre-Rule" column.
EPA conducted initial outreach to local environmental and community development organizations, local
government agencies, and individual community members involved in community organizing in all nine
communities. Between May and September 2022, EPA was able to meet with five of the identified
communities either virtually (indicated as "Virtual Meeting" in the "Proposal" column) or in a hybrid
virtual and in-person format (indicated as "Hybrid Meeting" in the "Proposal" column). EPA has not been
able to hold virtual or hybrid meetings with the remaining four communities (indicated as "Initial
Outreach" in the Proposal column) because of difficulties in finding community representatives who could
help with coordinating and planning an initial meeting; the Agency is continuing to consider whether and
how to engage with these communities. EPA is also soliciting comment in the proposed rule on whether
additional communities with identified PEJC should be included for future engagement.
Table 11. List of Affected Communities Chosen for Initial Public Meetings Based on the Results of
EPA's Air, Surface Water, and Drinking Water Screening Analyses
#
Screening Result
(Plant/Waterbody/PWS)
State
Screening
Analysis
Tier
Pre-
Rule
Proposal
1
EIA #667, Northside Generating Station
FL
Air
1
Virtual Meeting
2
EIA #3297, Wateree Station
SC
Air
1
Initial Outreach
3
EIA #2442, Four Corners Steam Electric
Station
NM
Air
1
YES
Virtual Meeting
4
COMID 10161978, Ohio River
(EIA#6071, Trimble County)
KY
Surface
Water
2
Virtual Meeting
5
COMID 6499098, Etowah River
(EIA# 703, Plant Bowen)
GA
Surface
Water
2
Initial Outreach
6
COMID 3124250, Rabbs Bayou
(EIA# 3470, W.A. Parish E.G.S.)
TX
Surface
Water
2
Hybrid Meeting
7
PWSID 84690510, Standing Rock Rural
Water System, Fort Yates
(EIA# 2817, Leland Olds Station)
ND
Drinking
Water
2
Initial Outreach
8
PWSID M10001800, City of Detroit
(EIA#6034, Belle River Power Plant and
EIA#1733, Monroe Power Plant)
Ml
Drinking
Water
2
Initial Outreach
9
PWSID NC0279010, NC0279030,
NC0279040, and NC3079031 Town of
Eden, Town of Madison,
Dan River Water Inc, Rockingham Co-
220 Corridor
(EIA# 8042, Belews Creek Steam Station)
NC
Drinking
Water
3
YES
Hybrid Meeting
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
7.4 Approach to Community Outreach
In advance of the public meetings for this effort, EPA identified several best practices for its initial
community outreach and engagement efforts. The sections below outline the process by which EPA
planned and prepared for public meetings, integrating these best practices.
7.4.1 Establishing Connections with Community Representatives
EPA attempted to leverage its limited resources by identifying and partnering with community
representatives who could organize meetings, host meetings (hybrid only), and reach out to community
members to encourage participation. Additionally, EPA recognized the value in partnering with
community representatives to alleviate community members' possible concerns about engaging directly
with a government agency.
To identify leaders in each of the communities chosen for public meetings, EPA first contacted
environmental organizations that had provided public comment on the 2020 rule, along with individuals
recommended by EJ Coordinators for the EPA regions where the communities were located. For most of
the communities, this approach yielded contact information for community representatives associated
with local environmental and community development organizations and local government agencies, as
well as individual community members involved in community organizing. For the remaining
communities, EPA also reached out to state environmental agencies and used online research to gather
contact information.
After collecting this information, EPA contacted and scheduled introductory calls with the community
representatives to provide them with background on the proposed rule, explain why EPA had chosen
their communities for initial outreach, and discuss the purpose of the potential meeting. After confirming
that the community representatives could help EPA plan a meeting and act as community partners to
elicit community participation, the Agency gathered information on the preferred meeting format, day of
the week, time of day, amount of advance notice, and any additional resources that might be needed to
ensure an accessible and beneficial meeting for community members. EPA then continued to meet with
community representatives as needed after the initial call to continue planning the meetings and
coordinating outreach materials.
7.4.2 Developing Outreach and Meeting Materials
EPA intended the public meetings to serve as opportunities for community members to learn about the
proposed rule and to provide meaningful input on regulatory preferences and impacts and concerns
related to steam electric power plants, along with input from other stakeholders, as it developed the
proposed rule. Accordingly, EPA developed a set of outreach materials describing the meeting and its
purpose, as well as the proposed rule.
One of these outreach materials was a one-page factsheet, provided to community members in advance
of the meeting. The factsheet's purpose was to communicate the following information simply and
concisely:
• What EPA, the ELG program, and the proposed rule are.
• The purpose of the meeting, general topics that would be discussed, and why their input mattered.
• How EPA would use the input, how the results of the analysis would be shared with the communities,
and what additional plans the Agency had for continued engagement with them.
• Contact information for EPA points of contact on the proposed rule.
To ensure that the factsheet would be clear to people across a broad range of literacy levels within and
among the communities selected for public meetings, EPA was mindful of using language at a fifth-grade
reading level and made use of pictures to communicate information where feasible.
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
In addition to the factsheet, EPA developed a presentation that was given to community members at the
beginning of each public meeting. The presentation expanded on the information included in the
factsheet, particularly information about the ELG program and the rulemaking. EPA included it at the
beginning of the meetings to ensure that all attendees had a baseline level of understanding about the
scope of the rulemaking and the purpose of the meeting so that they would be better able to provide
meaningful input. Additionally, the presentation gave community members the opportunity to ask EPA
questions about the rulemaking, how their information would be used, and how EPA would continue
engagement. This helped give transparency to the meetings that would be essential for creating an
environment where community members felt comfortable providing the Agency with their input.
After drafting the factsheet and presentation, EPA sent them to the community representatives for
review. Based on their feedback, EPA then revised the factsheet and presentation to improve the content
and ease of comprehension. For example, based on input from community representatives in Texas, EPA
provided English and Spanish versions of the factsheet and presentation to accommodate the Spanish-
speaking population in that area.
The factsheet and presentation are presented in Appendix C.
7.4.3 Preparing for Discussions with Community Members
Before the community meetings, EPA held calls with community representatives as well as EPA regional
staff and/or state government officials to discuss potential impacts or their concerns about the nearby
steam electric power plants, affected downstream surface waters, or drinking water systems.
Additionally, when available, EPA reviewed comments submitted as part of the permitting process for the
relevant plants to understand pre-existing impacts or concerns identified by community members.
7.4.4 Designing and Scheduling Community Meetings
EPA understood that to ensure communities could provide meaningful input, meetings needed to be
scheduled and held at a time and in a format that was convenient and accessible for community
members. To achieve this, EPA remained flexible in its approach to when and how the meetings were
held, allowing community representatives to guide the Agency's planning based on the specific needs in
their communities.
In meetings with community representatives, EPA received feedback on the appropriate time of day and
days of the week for the meetings to be held. For most of the communities EPA met with, evening
meetings were the most convenient: many community members work during the day and also have
childcare obligations that make morning and afternoon meetings difficult to attend. While preferred days
of the week varied by community, most communities advised EPA against scheduling meetings on specific
days of the week due to regularly scheduled religious or community activities.
EPA also received feedback from community representatives on the most accessible meeting formats for
their communities. The most accessible meeting formats for most communities were either virtual (via a
teleconferencing platform like Zoom or a conference call number) or hybrid, a combination in-person and
virtual meeting. Whether a virtual or hybrid meeting was held depended on each community's specific
needs, so EPA allocated resources during the planning process to build its capacity to host meetings in
both formats. Often, hybrid meetings were preferred in communities that did not have widespread
internet access and/or where community members felt more comfortable speaking with EPA in-person.
Additionally, EPA received input from community representatives about what resources they would need
provided to host the meetings and whether translation services would be needed. The need for resources
pertained mostly to the hybrid meetings, particularly with audio visual equipment, as venues chosen
based on their location and accessibility were not always equipped for hybrid meetings. EPA worked
closely with community representatives and its own contractors to identify and provide the needed
audio-visual equipment. For the hybrid meetings, EPA contractors also traveled with Agency staff to
provide on-site technical support. EPA also provided translation services when representatives indicated
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
that languages other than English were predominantly spoken in their communities. Based on the
community leaders' determinations, EPA provided in-person and virtual translation services for meetings
on a case-by-case basis.
7.5 Results of the Public Meetings
EPA held the community meetings beginning in May 2022. Across the five meetings, the Agency met with
a total of 80 community members. EPA followed a uniform structure for each meeting. Meetings began
with introductions by EPA staff and community representatives, along with a brief tutorial from Agency
contractors about how community members could participate, provide feedback, and resolve technical
issues virtually and in-person. Then EPA gave a presentation, providing an overview of the ELG program,
the proposed rule, and the purpose of the public meetings, after which the Agency answered questions
from community members on the content covered. Once all questions were answered, EPA began the
discussion portion of the meeting asking questions and soliciting input from community members on the
following topics:
• Ideas and strategies for limiting pollution from steam electric power plants
• Concerns from community members related to steam electric power plants and other sources of
pollution; nearby rivers, lakes, and streams; or their drinking water
• Community health, social or economic concerns.
The questions asked and the input received varied across communities based on the level of knowledge in
the community about the steam electric power plants and water pollution from the plants, as well as the
level of organization in the community around environmental issues. In meetings with communities
where there was widespread knowledge about water pollution issues related to steam electric power
plants and greater community organization around such issues, community members generally gave
prepared statements to EPA with detailed accounts of pollution concerns, community impacts, and
regulatory preferences. Meetings with communities with less knowledge about steam electric power
plants and water pollution issues needed more facilitation by EPA. In these meetings, feedback from
community members on pollution concerns and community impacts was less specific to plants and water
pollution; community members generally asked more questions about the rulemaking and what pollution
issues it could address, rather than having specific preferences for requirements to include in the
proposed rule underdevelopment.
An overview of the input received by EPA from community members is presented below. Detailed records
of the input received in each meeting can be found in Appendix D.
7.5.1 Regulatory Preferences
In the public meetings, community members shared their preferences on the stringency of the proposed
rule under development, requirements for specific discharges from steam electric power plants, and
additional requirements for steam electric power plants that could be incorporated into the proposed
rule.
In general, community members communicated their support for more stringent requirements on
wastewater discharges from steam electric power plants.
• In EPA's meeting with community members of the Navajo Nation, community participants stated that
they supported the most stringent regulations on wastewater discharges from steam electric power
plants. They recommended that EPA eliminate wastewater discharges-particularly BA transport
water-from steam electric power plants and regulate all pollutants in these wastewater discharges
through the proposed rule. They also expressed support for shorter compliance timeframes for steam
electric power plants in the proposed rule, as an added measure to reduce wastewater discharges.
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
• In North Carolina and Kentucky, community participants recommended that EPA incorporate zero
liquid discharge (ZLD) requirements for wastewater discharges into the proposed rule, with
participants in Kentucky noting that this should be required for all wastestreams from steam electric
power plants. Participants in North Carolina noted that EPA could recommend use of membrane
technologies in the proposed rule as it would enable steam electric power plants to quickly comply
with a ZLD requirement. Participants in Kentucky recommended that EPA eliminate a provision in the
2020 rule that allowed steam electric power plants to operate wet BA systems and purge 10 percent
of transport water by volume on a rolling monthly basis.
In addition to preferences for regulating wastewater discharges from steam electric power plants,
participants from across the communities that EPA met with expressed concerns about a lack of
information-sharing from the steam electric power plants in their communities.
• Participants in Kentucky, Texas, and North Carolina expressed concerns with a lack of data from the
plants on their discharges and the resultant pollutant loadings. Participants in Kentucky noted that
they only received marketing newsletters from their local plant and had no way to know if the
information is accurate. To address this, they stated the proposed rule should include a requirement
for steam electric power plants to post information to a publicly available website in a format
accessible to a general audience.
• In Texas, participants stated that they had access to general information on whether their local water
had pollutants exceeding federal limits but had no information on the specific impact of their local
plant on their water and soil, or of how widespread that impact is in their community. The
participants recommended that EPA make this kind of data from power plants publicly available so
community members can stay informed and avoid highly polluted areas.
• Community members in Florida also expressed concerns about accessibility of information on steam
electric power plants and stated that a regional EPA website with information specific to steam
electric power plants would be helpful. Additionally, they noted that there is an abundance of testing
or monitoring data available on pollutants, but that they would like information on the compliance of
the steam electric power plants to be made publicly available.
7.5.2 Environmental Concerns
In the community meetings, community members discussed environmental concerns related to their
local steam electric power plants as well as other sources of pollution.
A common environmental concern from the meetings was air pollution related to steam electric power
plants.
• Long-time community members in the Navajo Nation noted that, after their local plant opened, the
community began to experience air pollution and visible smog. This has not abated after the
installation of wet scrubber and other technologies: pollution controls are sometimes shut off at
night, allowing smog to be released overnight and thus creating hazes of pollution in the morning.
• Community members in Kentucky expressed concerns about air emissions from their local plant,
particularly their concerns about air pollutants eventually being deposited in soil and contaminating
local aquifers and surface water.
• A community member in Texas expressed concerns about a lack of air pollution controls at their local
plant.
• Concerns about air emissions from the local plant were also expressed by community members in
Florida.
Concerns related to pollution in surface water and groundwater from steam electric power plants were
another common environmental impact community members expressed to EPA in the meetings.
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
• Community participants in North Carolina expressed concerns about impacts to their local surface
water from plant discharges. Several years prior, a coal ash spill at their local plant contaminated their
local river with bromide and selenium. Community members have also collected surface water
samples themselves that have been found to have high levels of total trihalomethanes (TTHMs).
Because there are also concerns over groundwater contamination-many community members use
untreated well water for drinking water-residents primarily use bottled water for drinking water and
daily household activities.
• Community members in Kentucky expressed concerns related to discharges from their local plant and
potential impacts on the Ohio River, which they use for swimming and fishing. While drinking water
studies in Kentucky have not shown high levels of pollutants in drinking water, they were concerned
about water quality.
• Community members in Texas expressed concerns about leaching of pollutants from their local plant
into the groundwater. One community member reviewed groundwater monitoring well data for wells
around the local power plant and found that almost every well had pollutant levels exceeding federal
Maximum Contaminant Levels (MCLs). Community members also expressed concerns related to
water quality impacts in downstream lakes from plant discharges, as community members fish in
downstream waters of the plant and the water is used on lawns and at local parks.
• A Navajo Nation community member noted that after their local plant began operating, local surface
water became murky and polluted. Community members use this water for irrigation and drinking,
often boiling the water before using it for drinking and household activities. Community members
also had concerns related to water quantity impacts, stating that the local plant uses significant
amounts of water from local waters as cooling water.
• In Florida, a community member expressed concern over the potential for reverse tidal flow along a
local surface water to lead to discharges from the local plant contaminating the waterbody. This
waterbody was of particular concern because it is located in communities with minority and low-
income residents and also is affected by fecal coliform contamination.
In addition to air and water impacts, communities identified impacts to land and wildlife from steam
electric power plants as concerns.
• Navajo Nation community members expressed concerns about land pollution as a result of
inadequate handling of coal ash waste at their local plant, with particular concern that improper land
disposal will further pollute their local surface water.
• North Carolina community members expressed concerns related to coal ash contamination of soil.
They also stated that impacts on wildlife have been recorded after the coal ash spill from their local
plant, which killed 90 percent offish species in their local surface water-species that had previously
been a source of food for the community.
• Florida community members also expressed concern over contamination of sediment in their area
from discharges of pollutants from the local plant in the local surface water. Research by the
community showed materials, like mercury, had accumulated in the sediment around the surface
water. The community was also concerned about impacts to fish from pollutants discharged by the
local plant particularly because there are many subsistence fishers in their community (and Florida
residents generally consume a higher percentage offish and therefore require greater protections).
• In Kentucky, community members recommended that EPA consult with the U.S. Fish and Wildlife
Service to determine how discharges from local plants affect local wildlife and asked that EPA
consider wildlife impacts in the proposed rule.
Contributions of steam electric power plants to climate change was also mentioned as an environmental
impact of concern in EPA's meeting with Navajo Nation community members. Participants noted that
they are currently dealing with climate change-related issues including droughts and dust storms, which
they attribute to cumulative effects of pollution including from the local plant. A community member
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
noted that before the plant began operation, the desert had fields of flowers and reliable rain and
snowfall that provided needed precipitation; the current landscape is dry and barren with ecological dead
zones near the plant.
Aside from environmental impacts related to steam electric power plants, communities shared
information with EPA about other sources of pollution in their community, emphasizing the importance
of considering the cumulative risks that they face from multiple sources of pollution.
• Navajo Nation community members stated that they not only face pollution from steam electric
power plants but also pollution from the extractives industry including uranium, oil, helium, and coal-
particularly legacy pollution from waste disposal sites that have not been remediated.
• In Texas, community members stated additional impacts on air pollution, particularly ozone issues,
from the urban sprawl and traffic. Their local community is also surrounded by oil wells, chemical
plants, and a landfill that have had issues with leaching and polluting the land, which community
members were also concerned may lead to groundwater pollution and odor problems.
• In North Carolina, community participants expressed concerns related to legacy pollution from
industries no longer in the area like logging and textiles. They were also concerned about pollution
from industrial agriculture including E. coli from poultry operations and 1,4-dioxane applied to crops.
Additionally, the furniture industry in the area has caused concerns due to the lack of treatment of its
waste.
• Community members in Kentucky noted a local landfill and Superfund site as major environmental
concerns in the community. Community members worry about lead and per- and polyfluoroalkyl
substances (PFAS) leaching from the site and polluting their water. Community participants noted
orange leachate coming out of the ground and running into a nearby creek that community members
use for recreation. PFAS contamination from other sources was a concern for community members in
general.
• Community members in Florida also expressed interest in EPA considering cumulative effects of
pollutants in its distributional analysis, particularly the cumulative effects from water and air pollution
from the local power plant as well as pollution from coal ash stored at the local power plant. They
also mentioned another component of cumulative risks: storm surges during extreme weather
events, which they noted pose increasing challenges to their community.
7.5.3 Human Health and Safety Concerns
In each of the meetings that EPA held, communities expressed concerns to the Agency about safety and
health impacts related to pollution from steam electric power plants and provided the Agency with
information on general health issues in their communities.
• Navajo Nation community members expressed concerns related to health impacts from pollution
from the local steam electric power plant. They stated that air pollution from the plant and extractive
industries have led to chronic diseases associated with air pollution in their community noting
children with respiratory and cardiac problems-in particular, observable increases in asthma-and
people with cancer, emphysema, and chronic obstructive pulmonary disease (COPD). These types of
diseases, as one community member noted, take years to develop.
• In North Carolina, a community member noted that for a mile stretch near a lake affected by
pollution from the plant it is common for people living there to be a cancer survivor or to know
someone who has died from cancer.
• In Texas, a community member noted that a study conducted by Rice University on the benefits of
closing coal-fired power plants in Texas found that their local plant's particulate matter accounted for
about 178 statistical deaths a year, the highest of any coal-fired power plant in Texas. I
• In Florida, community members noted that a high number of children in their community suffer from
asthma.
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
In terms of general community health issues:
• Navajo Nation community members informed EPA that many people in their community have
physical and mental disabilities; the community has high rates of cancer, cardiovascular disease, and
obesity which may be exacerbated by pollution. A community member noted there are few hospitals
on the reservation which makes it difficult to travel to get medical care, especially with high gas
prices.
• In North Carolina, community members noted high rates of cancer, diabetes, skin disorders, and
reproductive issues in the community, as well as issues with bronchitis and asthma, especially among
children. Community members also experience difficulty with accessing health care as many residents
are uninsured.
• In Kentucky, community members expressed concerns related to the prevalence of cancer in their
community, particularly kidney and brain cancer. Participants informed EPA that a part of their
community with a high proportion of low-income and Black residents has high rates of illnesses like
cancer and many residents cannot afford high-quality medical care. It was found that residents in this
area tend to die 10 to 12 years earlier than residents in other parts of the community. In this part of
the community, participants also noted that EPA has told residents to put tarps on the ground before
letting their children play outside because of potential health risks.
In EPA's meeting with Navajo Nation community members, one former employee of the local steam
electric power plant expressed health and safety concerns related to working conditions at the plant. To
vacuum coal ash at the plant, they were given basic personal protective equipment (disposable face
mask, gloves, and safety glasses); even with this equipment, coal ash got all over them, including in their
eyes and mouth. They stated they and other workers were not taught about the composition of the coal
ash beforehand and were concerned about the health issues associated with it. They also described
instances of contractors climbing scaffolding of smokestacks without safety harnesses and noted reports
of gear and tools falling on employees.
7.5.4 Economic Impacts
Through the community meetings, particularly in North Carolina, EPA learned of widespread, long-term
economic impacts resulting from environmental impacts related to steam electric power plants.
North Carolina participants informed EPA that the community has experienced widespread economic
impacts due to pollution from the local plant, particularly after the coal ash spill. They noted many
residents have left the community due to water and soil contamination. This had had impacts on the
community, particularly through school closures due to a lack of students. The water and soil pollution
has also caused a drop in home values-meaning that some residents cannot leave the community or
move to other areas within it because banks have stopped providing home loans. Because of fears related
to bromide and selenium in their drinking water after the coal ash spill, many residents exclusively use
bottled water: a large expense, as residents noted, given that many residents are low-income.
Additionally, participants informed EPA that water pollution from the coal ash spills has affected the
tourism industry, the largest employer in their community and one centered around the recreational
opportunities in their local waterbodies. Community members also suspected that the departure of a
Miller-Coors plant-which caused the community to lose 300 jobs-was the result of the water
contamination from the plant.
Navajo Nation community members also informed EPA of economic impacts in their area. A lack of
dependable water has negatively affected farming, they stated. Community members rely on farming for
subsistence and their livelihoods, and some people have been forced to sell their animals for income.
Community members also noted the role that the local plant plays as an employer in the community.
Participants noted that the plant is one of the major providers of well-paying jobs and that the majority of
the people working at the plant are tribal members. Despite this, some participants remarked that the
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Section 7—Engagement with Communities with Potential Environmental Justice Concerns
economic, environmental, and human health impacts of the pollution from the plant outweigh the
employment benefits.
In Florida, participants noted that one of the foundations of their community is the fishing community
and industry, particularly for blue crab and other seafood. Additionally, recreational activities, including
fishing, marinas, and dining, occur close to the local plant. Within a three-mile radius of the plant, there
are state and city parks where preservation and recreational activities occur, including swimming and
walking trails. Community members noted that the industries, activities, and people in these areas can all
be affected by pollutant discharges from the local plant.
7.5.5 Cultural and Spiritual Impacts
In the meeting with Navajo Nation community members, EPA learned how environmental degradation
from the local steam electric power plant's pollution has culturally and spiritually affected the
community. The San Juan River, affected by pollution, is a male river and a provider to the Dine people.
7.5.6 Communication and Public Outreach
Community members also provided EPA with recommendations to consider when communicating
information about the proposed rule and conducting future meetings in their communities.
In Kentucky, community members emphasized that EPA should use communication platforms other than
the rule's website. They suggested EPA consider publishing a press release, written for the general public,
in their local newspaper as well as submitting an announcement to a local radio station. Additionally,
because there is a substantial Spanish-speaking population in their community, EPA should offer any
published materials on the proposed rule in Spanish to better inform this population. In North Carolina,
community members also expressed the need for EPA to use alternative communication platforms.
Because the community has no printed newspaper and limited access to internet, they said EPA should
consider mail-based, radio, and door-to-door canvassing.
In Florida, community members emphasized expanding community outreach for future public meetings
on the proposed rule in a targeted manner. They suggested that EPA reach out to several community
groups, including the Jacksonville NAACP and Duval County Soil and Water, as well as city council
members that can pass information along to their constituents. Community members also noted that EPA
might increase participation if, in its outreach, it discusses the meeting and proposed rule in a simple and
easy format; they also suggested focusing on discussing the rule through a local framework, e.g.,
discussing impacts of the rule to the angling community. Additionally, more emphasis on explaining EJ
would be helpful: many participants stated that EJ is not a widely understood concept in their community.
7.5.7 Concerns Relevant to Other EPA Regulatory Actions
In addition to information related to the proposed rule, community members expressed concerns about
steam electric power plants that are outside the rule's scope but may be relevant for other EPA
regulatory actions related to steam electric power plants.
• Navajo Nation meeting participants noted concerns that the disposal of coal combustion residuals
(CCR) from their local plant had potentially contaminated their local waterways, which they use for
recreation and agriculture, due to poor monitoring and handling of disposal by the owner of the
plant. They stated that many of the coal ash pits are unlined; they were not aware of water quality
monitoring by the plant or the regulatory community.
• In Texas, community members expressed concerns about groundwater contamination from landfills
and surface impoundments. Participants did not trust that their local plant had stopped intaking coal
ash in its surface impoundments and was monitoring groundwater as required by EPA's CCR rule.
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8. Regulatory Options
This analysis evaluates four regulatory options and identifies one preferred option (Option 3), as shown in
Table 12. All options include the same technology basis for CRL (chemical precipitation) and legacy
wastewater (best professional judgment [BPJ]) while incrementally increasing controls on FGD
wastewater, BA transport water, or both. Each successive option from Option 1 to 4 would achieve a
greater reduction in wastewater pollutant discharges. Each subcategorization is described further in
Section VII.C of the preamble.
8.1 FGD Wastewater
Option 1 would eliminate the best available technology economically achievable (BAT) and pretreatment
standards for existing sources (PSES) subcategorizations for high-FGD-flow facilities and low-utilization
electric generating units (LUEGUs). The effect would be establishment of the same mercury, arsenic,
selenium, and nitrogen limitations applicable to the industrial category based on chemical precipitation
followed by low-hydraulic-residence-time biological treatment and ultrafiltration. Options 2 and 3 would
eliminate the BAT and PSES subcategorizations for high-FGD-flow facilities and LUEGUs and further would
require zero discharge of FGD wastewater based on chemical precipitation followed by membrane
filtration with 100 percent recycle of the permeate. These options would also create a subcategory for
early adopters that have already installed compliant biological treatment systems and would retire no
later than December 31, 2032. Option 4 would establish an industry-wide zero discharge requirement
without establishing an early adopter subcategory. Note that all four options would retain the
subcategory for electric generating units (EGUs) permanently ceasing coal combustion by 2028.
8.2 BA Transport Water
Options 1 and 2 would eliminate the BAT and PSES subcategorization for LUEGUs. The effect would be
establishment of the same volumetric purge limitation applicable to the industrial category based on
high-recycle-rate systems. Option 3 incorporates zero discharge based on dry handling or closed-loop
systems. This option would also create a subcategory for early adopters that have already installed a
compliant high-recycle-rate system and would retire no later than December 31, 2032. Option 4 would
establish an industry-wide zero discharge requirement without establishing an early adopter subcategory.
All four options retain the subcategory for EGUs permanently ceasing coal combustion by 2028.
8.3 CRL
All four options would establish BAT limitations and PSES for mercury and arsenic based on chemical
precipitation treatment.
8.4 Legacy Wastewater
None of the four options specify a nationwide technology basis for BAT/PSES applicable to such
wastewater at this time. Rather, they allow such limitations to be derived on a site-specific basis by the
permitting authorities, using their BPJ.
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Section 8—Regulatory Options
Table 12. Regulatory Options Analyzed for the Proposed Rule
Technology Basis for BAT/PSES Regulatory Options (a)
2020 Rule
Wastestream Subcategory (Baseline) Option 1 Option 2 Option 3 Option 4
FGD Wastewater
NA (default unless in
subcategory) (b)
CP + Bio
CP + Bio
CP +
Membrane
CP +
Membrane
CP +
Membrane
Boilers permanently
ceasing the combustion
of coal by 2028
SI
SI
SI
SI
SI
Early adopters or boilers
permanently ceasing the
combustion of coal by
2032
NS
NS
CP + Bio
CP + Bio
NS
High FGD Flow Facilities
or Low Utilization Boilers
CP
CP + Bio
CP +
Membrane
CP +
Membrane
CP +
Membrane
Bottom Ash
Transport Water
NA (default unless in
subcategory) (b)
HRR
HRR
HRR
ZLD
ZLD
Boilers permanently
ceasing the combustion
of coal by 2028
SI
SI
SI
SI
SI
Early adopters or boilers
permanently ceasing the
combustion of coal by
2032
NS
NS
NS
HRR
NS
Low Utilization Boilers
BMP Plan
HRR
HRR
ZLD
ZLD
CRL
NA (default) (b)
BPJ
CP
CP
CP
CP
Abbreviations: BA = Bottom Ash; BMP = Best Management Practice; BPJ = Best Professional Judgement; CP = Chemical
Precipitation; HRR = High Recycle Rate Systems; SI = Surface Impoundment; ZLD = Zero Liquid Discharge; NS = Not subcategorized
(default technology basis applies); NA = Not applicable
Notes:
a- See the Technical Development Document (TDDJ for a description of these technologies (U.S. EPA, 2023e).
b- This table does not present existing subcategories included in the 2015 and 2020 rules as EPA did not reopen the existing
subcategorization of oil-fired units or units with a nameplate capacity of 50 megawatts or less.
Source: U.S. EPA Analysis, 2023
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9. Distributional Analysis of Pollutant Exposures
For the proposed rule, EPA evaluated the distribution of pollutant exposures and health effects among all
communities potentially affected under the baseline and each of the regulatory options identified in
Section 8. EPA conducted this analysis for each of the relevant pathways of exposure to pollutants from
steam electric power plants: air (only analyzes Option 3), surface water, and drinking water.
The objectives of this analysis were to determine:
• Whether, through each exposure pathway, under the baseline, communities with identified PEJC
experience disproportionately high and adverse pollutant exposures and/or health effects compared
to communities with no identified PEJC.
• Whether disproportionately high and adverse pollutant exposures and health effects experienced by
communities with PEJC were mitigated, exacerbated, or created by each of the regulatory options.
The results of these analyses are presented and discussed in this section.
9.1 Analysis of Exposures to Air Pollutants from Steam Electric Power Plants
EPA analyzed air pollutant exposures24 across all communities potentially affected by the proposed rule to
evaluate whether population groups of concern experience disproportionately high and adverse
exposures, compared to relevant comparison population groups, under the baseline and preferred
regulatory option (Option 3). The analysis focuses on PM2.5 and ozone exposures25 from emissions from
the steam electric power plants regulated under the proposed rule.
EPA's approach to this analysis considered the proposed regulatory provisions of Option 3, as well as the
nature of known and potential exposures and impacts. As the proposed rule would regulate steam
electric power plants across the U.S., which typically have tall stacks and thus disperse emissions over
large distances, it was appropriate to conduct a national-scale distributional analysis of PM2.5 and ozone
exposures. Using modeled baseline and policy PM2.5 and ozone air quality surfaces, EPA analyzed changes
in PM2.5 and ozone concentrations resulting from the emission changes projected by the Integrated
Planning Model (IPM)26 to occur under the proposed rule as compared to the baseline, characterizing
average and distributional exposures both prior to and following implementation of Option 3 in 2030.
Population characteristics considered in the distributional analysis were race, ethnicity, poverty status,
linguistic isolation, educational attainment, age, and sex (Table 13).27
24 The term "exposure" is used here to describe estimated PM2.5 and ozone concentrations, not individual dosage.
25, Air quality surfaces used to estimate exposures are based on 12-kilometer x 12-kilometer grids. More
information on air quality modeling can be found in Chapter 8 of the 2023 BCA.
26, As discussed in greater detail in U.S. EPA (2018a), IPM is a comprehensive electricity market optimization model
that can evaluate the impacts of regulatory actions affecting the power sector within the context of regional
and national electricity markets. IPM generates least-cost resource dispatch decisions based on user-specified
constraints such as environmental, demand, and other operational constraints. It uses a long-term dynamic
linear programming framework that simulates the dispatch of generating capacity to achieve a demand-supply
equilibrium on a seasonal basis and by region. The model computes optimal capacity that combines short-term
dispatch decisions with long-term investment decisions. IPM runs under the assumption that electricity demand
must be met and maintains a consistent expectation of future load. IPM outputs include the air emissions
resulting from the simulated generation mix. Refer to the 2023 Regulatory Impact Analysis (RIA) report for more
details on the IPM model runs.
27, Population projections stratified by race/ethnicity, age, and sex are based on economic forecasting models
developed by Woods and Poole (2015). The Woods and Poole database contains county-level projections of
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Section 9—Distributional Analysis of Pollutant Exposures
Table 13. Population Characteristics Included in the Ozone and PM2.5 Distributional Analyses
Demographic Characteristics
Description
Race
Asian; American Indian; Black; White
Ethnicity
Hispanic; Non-Flispanic
Educational Attainment
Over age 24 with a high school degree or more; Over age 24 with no high
school degree
Poverty Status
Above /below 200% of the poverty line; Above/below the poverty line
Linguistic Isolation
Speaks/does not speak English "very well or better"; Speaks/does not speak
English less than "well or better"
Age
Children (0-17); Adults (18-64); Older Adults (65-99)
Sex
Female; Male
Important caveats of this analysis include:
• PM2.5 and ozone concentration changes associated with Option 3 are relatively small in magnitude. As
a result, the potential for Option 3 to mitigate or exacerbate existing PEJC is small.
• Although several future years were assessed for health benefits associated with this proposed
rulemaking, there was variability in high year-to-year PM2.5 and ozone concentration change across
modeled future years. Only 2030 is analyzed for air pollutant distributional implications because 2030
is the nearest future year in which all affected steam electric power plants are expected to be in
compliance with Option 3.
9.1.1 Analysis of Changes in Air Quality Across Affected Areas of the Contiguous U.S.
As IPM predicts, Option 3 will lead to both decreases and increases in emissions in 2030. Given this, to
characterize changes in emissions of PM2.5 and ozone across the contiguous U.S., EPA grouped affected
areas into those where air quality does not change, improves, or worsens as a result of Option 3. As air
quality changes associated with Option 3 were estimated to be small, EPA used a cutoff of changes in
concentrations that were at least a thousandth of each pollutant's National Ambient Air Quality Standard
(NAAQS) ( +/- 0.007 ppb of ozone and 0.0012 |ag/m3 of PM2.5) to define "changing" air quality.
In 2030, 365 million people are predicted to live in the contiguous U.S.. Applying the groupings and
definition of changing air quality, the results of the IPM analysis show that, under Option 3, about 40
percent and 50 percent of the U.S. population, respectively, resides in areas predicted to experience
changes in ozone and PM2.5 concentrations compared to the baseline (Figure 1). In the areas where air
quality changes are predicted under Option 3, 99 percent (144.5 million) and 85 percent (155 million) of
the population, respectively, is predicted to experience air quality improvements for ozone and PM2.5
compared to the baseline (Figure 1). Additionally, in the areas where air quality changes are predicted
under Option 3, one percent (1.5 million) and 15 percent (30 million) of the population, respectively, is
predicted to experience worsening air quality for ozone and PM2.5 compared to the baseline (Figure 1).
EPA notes that ozone and PM2.5 changes under Option 3 in areas experiencing worsening air quality are
predicted to be small compared to the baseline, averaging approximately 0.01 ppb for ozone and 0.002
|ag/m3 for PM2.5. Additionally, while increases in PM2.5 concentrations under Option 3 are predicted for a
population by age, sex, and race out to 2050, relative to a baseline using the 2010 Census data. Population
projections for all U.S. counties are determined simultaneously to consider patterns of economic growth and
migration. County-level estimates of population percentages within the poverty status and educational
attainment groups were derived from 2015 to 2019 five-year average ACS estimates. More information can be
found in Appendix J of the BenMAP-CE user's manual (https://www.epa.gov/benmap/benmap-ce-manual-and-
appendices).
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Section 9—Distributional Analysis of Pollutant Exposures
nontrivial number of people in 2030, EPA notes that increases in PM2.5 concentrations in later modeled
future year scenarios not included in this analysis (2035, 2040, 2045, and 2050) occur in substantially
fewer areas.
40
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Section 9—Distributional Analysis of Pollutant Exposures
Area
Pollutant
Contiguous U.S. Ozone
PM2.5
Not Changing Ozone
PM2.5
Changing Ozone
PM2.5
Worsening Ozone
Improving Ozone
PM2.5
PM2.5
OM 50M 100M 150M 200M 250M 300M 350M
Population Count
Figure 1. Number of People in the Contiguous U.S. Residing in Areas with Not Changing, Changing,
Improving, and Worsening Modeled Ozone and PM2.5 Concentrations in 2030
9.1.2 Distribution of Ozone Exposures in Communities with Predicted Changes in Air Quality
For areas with predicted changes in ozone concentrations under Option 3, EPA conducted a distributional
analysis to determine whether population groups of concern experience disproportionately high and
adverse exposures to ozone relative to their relevant comparison population groups under the baseline
and whether such PEJC are mitigated, exacerbated, or created under Option 3.
As described in Chapter 8 of the 2023 BCA, higher ozone exposure is associated with a wide range of
adverse health effects, including premature mortality; respiratory effects, including increases in hospital
admissions and emergency room visits, asthma onset and symptom exacerbation, allergic rhinitis (hay
fever) symptoms; cardiovascular and nervous system effects; and reproductive and developmental
effects. Thus, reducing exposure to ozone can provide both health and economic benefits, whose
significance may depend on socioeconomic factors (e.g., susceptibility or vulnerability according to
income or race/ethnicity, access to healthcare).
Figure 2 is a map of the areas with predicted changes in ozone concentrations under Option 3 in 2030.
The map shows areas in which the warm season (April - September) MDA8 ozone concentrations
improve (shown in green) or worsen (shown in red) - by at least +/- 0.007 ppb - under Option 3.
41
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Section 9—Distributional Analysis of Pollutant Exposures
Figure 2. Map of 12-km Grid Cells with Modeled Changes in MDA3 Warm Season Ozone
Concentrations-Improving (Green) or Worsening (Red)-by at Least +/-0.007 ppb in 2030
In areas shown as having predicted improvements in air quality in 2030, decreases in ozone are driven by
the net reduction in regional NOx emissions from the steam electric power generating sector as a result of
Option 3. In areas shown as having predicted worsening air quality in 2030, increases in ozone are the
result of a relatively small number of sources with predicted increases in NOx emissions under Option 3
due to IPM-projected changes in the future dispatch of certain electricity generation units after
promulgation of the proposed rule.
Comparing the baseline concentrations of MDA8 ozone in areas with predicted changing ozone
concentrations under Option 3 to the baseline concentrations of MDA8 ozone in areas with no predicted
change in ozone concentrations, EPA found that areas not affected by ozone changes from Option 3 have,
on average, higher baseline MDA8 ozone concentrations (Figure 3). Additionally, the areas expected to
experience worsening ozone concentrations under Option 3 have lower baseline average ozone
concentrations than any other group (Figure 3). As the population in areas with changing ozone
concentrations under Option 3 is nearly identical to the population in areas with improving ozone
concentrations under Option 3, the two dots overlap in Figure 3.
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Section 9—Distributional Analysis of Pollutant Exposures
Contiguous U.S. 0
300M-
c
o
Not Changing O
Reference j? 200M-
(0-99) g
c
a.
Changing
'improving
100M-
0M- OWorsening
39
40
Ozone(ppb)
41
42
Figure 3. Baseline MDA8 Ozone Concentrations and Population Counts in Areas with Not Changing,
Changing, Improving, and Worsening Modeled Ozone Concentrations in 2030
To determine whether PEJC were present under the baseline and whether they were mitigated,
exacerbated, or created by Option 3, EPA modeled average baseline warm season MDA8 ozone
concentrations and MDA8 ozone concentration changes under Option 3 across population groups of
concern compared to the overall reference group (labelled "Reference [0-99]") and their relevant
comparison groups (e.g., White for racial or ethnic groups). Different areas, air quality scenarios, and
methods of showing results are presented across the columns in Table 1428, all overlaid with intensifying
color gradients to support visualizing differences. The green color gradient applies to columns presenting
total exposure burden and the gray gradient to columns presenting the absolute or percent change in
exposure when moving from the baseline scenario to the policy scenario. More information on the
columns in Table 14 can be found in Table 15.
28, Numbers in Table 13 extend two and three places beyond the decimal point due to the small magnitude of air
quality changes; this is not intended to convey confidence in EPA's ability to estimate air quality exposures to
that level of exactness.
43
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Section 9—Distributional Analysis of Pollutant Exposures
Table 14. Modeled MDA8 Ozone Concentrations (ppb) Across Area Categories and Selected Population Groups in 2030
Population
Groups
Population (Ages)
1. Contiguous U.S.
Baseline
2. Contiguous U.S.
Policy
3, Changes in
Contiguous U.S.
4, % Change in
Contiguous U.S.
5. Baseline Areas
Changing
6. Policy Areas
Changing
7, Changes in Policy
Areas Changing
8. % Changes in
Changing Areas
9. Baseline Areas
Improving
10. Policy Areas
Improving
11. Changes in
Improving Areas
12. % Changes in
Improving Areas
13, Baseline Areas
Worsening
14. Policy Areas
Worsening
15. Changes in
Worsening Areas
16. % Changes in
Worsening Areas
17. Areas Not
Changing
Reference
Reference (0-93)
40.93
40.32
0.007
0.017
33.43
33.42
0.014
0.036
33.44
33.43
0.014
0.036
38.54
38.55
-0.011
-0.023
41.99
Race
White (0-99)
41.02
41.02
0.007
0.017
33.40
39.38
0.014
0.036
39.40
33.33
0.014
0.036
38.65
38.66
-0.011
-0.023
42.12
American Indian (0-99)
43.02
43.02
0.004
0.008
38.87
38.86
0.013
0.033
38.81
38.80
0.014
0.035
40.88
40.89
-0.010
-0.024
44.15
Asian (0-99)
42.00
42.00
0.005
0.012
40.45
40.44
0.012
0.030
40.46
40.45
0.013
0.031
33.73
33.74
-0.011
-0.023
42.81
Black (0-99)
39.67
39.66
0.009
0.022
39.25
39.24
0.014
0.036
39.28
39.26
0.015
0.038
37.99
38.00
-0.011
-0.030
40.16
Ethnicity
Non-Hispanic (0-99)
40.41
40.40
0.008
0.020
33.34
33.33
0.014
0.036
33.35
33.33
0.014
0.037
38.48
38.49
-0.011
-0.023
41.35
Hispanic (0-99)
42.77
42.77
0.004
0.009
40.10
40.03
0.013
0.031
40.11
40.10
0.013
0.032
39.08
39.09
-0.012
-0.030
43.54
Educational
Attainment
More educated (>24: HS or more)
40.76
40.75
0.007
0.018
33.45
39.44
0.014
0.035
39.46
33.45
0.014
0.036
38.50
38.51
-0.011
-0.023
41.73
Less educated (>24; no HS)
41.33
41.33
0.006
0.015
33.28
39.27
0.014
0.036
39.29
33.28
0.014
0.036
38.18
38.13
-0.011
-0.030
42.56
Poverty
Status
>200^ of the poverty line (0-99)
40.93
40.92
0.007
0.017
39.55
39.53
0.014
0.035
39.56
39.54
0.014
0.036
38.59
38.60
-0.011
-0.023
41.93
<200:^ of the poverty line (0-99)
40.31
40.31
0.007
0.017
33.13
33.17
0.014
0.037
33.13
33.18
0.015
0.037
38.44
38.45
-0.011
-0.023
42.09
> Poverty line (0-99)
40.93
40.92
0.007
0.017
39.47
39.46
0.014
0.035
39.48
39.47
0.014
0.036
38.53
38.55
-0.011
-0.029
41.95
< Poverty line (0-99)
40.93
40.32
0.007
0.017
33.21
33.20
0.014
0.037
33.22
33.20
0.015
0.037
38.54
38.55
-0.011
-0.028
42.14
Linguistic
Isolation
English "very well or better" (0-99)
40.81
40.80
0.007
0.018
33.38
39.37
0.014
0.036
39.33
33.37
0.014
0.037
38.50
38.51
-0.011
-0.029
41.88
English < "very w ell" (0-99)
42.14
42.14
0.004
0.010
40.25
40.24
0.012
0.030
40.26
40.25
0.012
0.031
33.30
33.31
-0.012
-0.030
42.86
English "well or better" (0-99)
40.86
40.86
0.007
0.017
33.41
33.33
0.014
0.036
33.42
33.40
0.014
0.036
38.53
38.54
-0.011
-0.023
41.93
English< "well" (0-99)
42.19
42.18
0.004
0.010
40.24
40.22
0.012
0.030
40.24
40.23
0.012
0.031
39.10
39.11
-0.012
-0.030
42.88
Age
Children (0-17)
41.15
41.14
0.007
0.017
33.45
39.43
0.014
0.036
39.46
33.44
0.014
0.036
38.60
38.61
-0.011
-0.023
42.32
Adults (18-64)
40.98
40.97
0.007
0.017
33.46
39.45
0.014
0.035
39.47
39.46
0.014
0.036
38.59
38.61
-0.011
-0.029
42.05
Older Adults (65-99)
40.53
40.52
0.007
0.018
33.32
39.30
0.014
0.036
39.32
33.31
0.014
0.036
38.27
38.28
-0.011
-0.029
41.43
Sen
Females (0-99)
40.92
40.91
0.007
0.017
33.45
39.43
0.014
0.036
39.46
33.44
0.014
0.036
38.53
38.54
-0.011
-0.029
41.38
Males (0-99)
40.94
40.93
0.007
0.017
33.41
39.40
0.014
0.036
39.42
39.41
0.014
0.036
38.55
38.56
-0.011
-0.029
42.00
44
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Section 9—Distributional Analysis of Pollutant Exposures
Table 15. Additional Information on the Column Headers Used in Table 14
1. Contiguous U.S. Baseline
Average exposure burden under the baseline scenario averaged across the population in the entire contiguous
2. Contiguous U.S. Policy
Average exposure burden underthe policy scenario averaged across the population In the entire contiguous U.S.
3. Changes in Contiguous U. S.
Average exposure changes when moving from the baseline to the policy scenario'averaged across the
population in the entire contiguous U.S.
4. % Change in Contiguous U.S.
Average exposure changes as a percent of baseline exposure when moving from the baseline to the policy
scenario averaged across the population in the entire contiguous U.S.
5, Baseline Areas Changing
Average exposure burden underthe baseline scenario averaged across the population experiencing a change of
at (east 1/1000th of the \AAQS
6. Policy Areas Changing
Average exposure burden underthe policy scenario averaged across the population experiencing a change of at
least 1/lOQOth of the NAAQS
7. Changes in Policy Areas Changing
Average exposure changes when moving from the baseline to the policy scenario averaged across the
population experiencing a change of at least 1/I000th of the \AAQS
8. %¦ Changes in Changing Areas
Average exposure changes as a percent of baseline exposure when moving from the baseline xo the policy
scenario averaged across the population experiencing a change of at least 1/I000th of the NAAQS
9. Baseline Areas Improving
Average exposure burden underthe baseline scenario averaged across the population experiencingan air
quality improvement of at least l/1000th of the NAAQS
10. Policy Areas Improving
Average exposure burden under the policy scenario averaged across the population experiencing an air quality
improvement of at least 1/I000th of the NAAQS
11. Changes in Improving Areas
Average exposure changes when moving from the baseline to the policy scenario averaged across the
population experiencing an air quality improvement of at least l/1000th of the NAAQS
12. % Changes in Improving Areas
Average exposure changes as a percent of baseline exposure when moving from the baseline to the pol'cy
scenario averaged across the population experiencingan air quality improvement of at least 1/lOOOth of the
13. Baseline Areas Worsening
Average exposure burden underthe baseline scenario averaged across the population experiencing an air
quality worsening of at ieast i/'1000th of the NAAQS
14. Policy Areas Worsening
Average exposure burden underthe policy scenario averaged across the population experiencing an air quality
worsening of at ieast l/i000th of the NAAQS
15. Changes in Worsening Areas
Average exposure changes when moving from the baseline to the policy scenario averaged across the
population experiencing an air quality worsening of at ieast l/1000th of the NAAQS
16. % Changes in Worsening Areas
Average exposure changes as a percent of baseline exposure when moving from the baseline to the policy
scenario averaged across the population experiencing an air quality worsening of at least 1/I000th of the NA^u
17, Areas Not Changing
Average exposure burden underthe areas not changing or changing by less than 1/1000th of the NAAQS
45
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Section 9—Distributional Analysis of Pollutant Exposures
Based on the results of the analysis, EPA determined that Option 3 leads to small changes in MDA8 ozone
concentrations. Across the contiguous United States, the average total warm-season MDA8 ozone
concentrations under the baseline and Option 3 (shown in columns 1 and 2 in Table 14) are similar when
averaged across the lower 48 states. The absolute magnitude of these changes is less than 0.01 ppb, or
about a 0.01-0.02 percent change from baseline concentrations, as shown in the first and second gray-
shaded columns in Table 14. Columns 5-8 in the table show MDA8 concentrations in changing areas,
which includes both areas in which MDA8 ozone concentrations improve (shown in columns 9-12) and
areas in which they worsen (shown in columns 13-16).29 Column 17 shows MDA8 ozone concentrations
by population group in the areas that are not affected by the proposed rule.
Given that baseline MDA8 ozone concentrations for Option 3 are similar to those for other recent
rulemakings (e.g., the regulatory impact analysis [RIA] for the proposed federal implementation plan on
ozone transport for the 2015 ozone NAAQS (U.S. EPA., 2022g) and areas changing can be more
meaningfully discussed by directly addressing improving and worsening areas, columns 1-8 in Table 14
are not discussed in detail here.30
Although there are differences in baseline exposures across population groups and area categories, the
absolute and relative changes across population groups of concern in improving and worsening areas
under Option 3 are similar (shown in columns 11-12 and 15-16 in Table 14). This suggests that MDA8
ozone exposure disparities are not created, exacerbated, or mitigated under Option 3 as compared to the
baseline.
To further evaluate distributional impacts, EPA evaluated differences in MDA8 ozone exposures across
the various population groups of concern compared to their relevant comparison groups. Figure 4 shows
the results. For total exposures (columns 1, 2, 4, 5, 7, 8, 10, 11, and 13 in the figure), colored lines to the
right and left of the black line indicate differentially high and low exposures in the population group of
concern relative to the comparison group. For exposure changes (columns 3, 6, 9, and 12), colored lines
to the right and left of the black line indicate differentially large and small exposure reductions in the
population group of concern relative to the comparison group.
29, In other EJ and benefits assessments, air quality improvements have been shown as positive numbers. In
keeping with this precedent, worsening air quality concentrations are presented as negative numbers here.
3a For a discussion, see the Regulatory Impacts Analysis for the Proposed Federal Implementation Plan Addressing
Regional Ozone Transport for the 2015 Ozone NAAQS (U.S. EPA, 2022g).
46
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Section 9—Distributional Analysis of Pollutant Exposures
Population
Groups
Reference
Race
Ethnicity
Linguistic
Isolation
Age
Sex
1. Contiguous 2. Contiguous
U.S. Baseline U.S. Policy
3. Changes in
Contiguous
U.S.
„ §100%"
C t;
ii i 50%-
aj q.
<£ o%.
„ §100%'
£ -i 50%-
0) Cl
i° o%.
s §100%'
£ "3 S0%-
*1 0%.
„ §100%"
t; | 5o%-
4. Baseline
Areas
Changing
5. Policy
Areas
Changing
6. Changes in
Areas
Changing
7. Baseline
Areas
Improving
8.Policy Areas
| Improving
9. Changes in 10. Baseline 11. Policy 12. Changes
Improving Areas Areas in Worsening
Areas Worsening Worsening Areas
13. Areas Not
Changing
a _
-------
Section 9—Distributional Analysis of Pollutant Exposures
9.1.3 Distribution of PM2.s Exposures in Communities with Predicted Changes in Air Quality
In areas with predicted changes in PM2.5 concentrations under Option 3, EPA conducted a distributional
analysis to determine whether population groups of concern experience disproportionately high and
adverse exposures to annual average PM2.5 concentrations as compared to their relevant comparison
groups under the baseline and whether such PEJC are mitigated, exacerbated, or created under Option 3.
As described in Chapter 8 of the 2023 BCA, higher PM2.5 exposure is associated with a wide range of
adverse health effects, including:
• Premature mortality.
• Cardiovascular effects such as heart attacks, strokes, and increased hospital admissions or emergency
department visits due to cardiovascular problems.
• Respiratory effects, including hospital admissions or emergency department visits, and onset or
exacerbation of asthma symptoms, lung cancer, and allergic rhinitis (hay fever) symptoms.
• Alzheimer's disease.
• Parkinson's disease.
• Other nervous system effects (e.g., autism, cognitive decline, dementia).
• Metabolic effects (e.g., diabetes).
• Reproductive and developmental effects (e.g., low birth weight, pre-term births).
• Cancer, mutagenicity, and genotoxicity effects.
Thus, reducing exposure to PM2.5 provides both health and economic benefits on populations, with the
significance of the benefits depending on socioeconomic factors (e.g., susceptibility or vulnerability
among subgroups according to income or race/ethnicity, access to healthcare).
Figure 5 is a map of the areas with predicted changes in average annual PM2.5 concentrations under
Option 3 in 2030. The map shows areas in which the average annual PM2.5 concentrations improve
(shown in blue) or worsen (shown in red)-by at least +/- 0.0012 |ag/m3-under Option 3.
48
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Section 9—Distributional Analysis of Pollutant Exposures
Figure 5. Map of 12-Kilometer Grid Cells with Modeled Average Annual PM2.5 Concentrations
Improving (Blue) or Worsening (Red) by at Least +/-0.0012 ng/m3 in 2030
EPA found that changes in PM2.5 emissions are driven by changes in the types of steam EGUs that are
being dispatched in any given future year. In certain out-years, higher-emitting units may be dispatched
to meet generation needs, which could result in PM2.s emissions increases in those particular years.
Figure 6 shows the average annual baseline PM2.5 concentrations for the areas in the contiguous United
States that are affected by Option 3.
49
-------
Section 9—Distributional Analysis of Pollutant Exposures
350M-
# Contiguous U.S.
300M-
c 250M-
o
(0-99)
Reference
| 200M-
O Changing
O Improving
Q.
O
# Not Changing
a 150M-
100M-
50M-
WorseningQ
OM
7.0 7.1 7.2 7.3 7.4 7.5 7.6 7.7
PM2.s (Lig/m3)
Figure 6. Baseline Average Annual PM2.5 Concentrations and Population Counts in Areas with Not
Changing, Changing, Improving, and Worsening Modeled Ozone Concentrations in 2030
Comparing baseline average annual PM2.5 concentrations in areas with predicted change in PM2.5
concentrations under Option 3 to baseline average annual PM2.5 concentrations in areas with no
predicted change in PM2.5 concentrations under the baseline, EPA found that-as with MDA8 ozone
concentrations-the baseline average annual PM2.5 concentrations in areas with no predicted change were
higher than in areas with a predicted change. Unlike with MDA8 ozone concentrations, areas predicted to
experience worsening PM2.5 concentrations under Option 3 had higher baseline average annual PM2.5
concentrations than all other area categories analyzed. However, EPA notes that very few areas are
predicted to have increased average annual PM2.5 concentrations due to Option 3 in modeled future
years after 2030. Additionally, average annual PM2.5 concentration increases in these areas are on average
0.002 pg/m3; this is considered to be a small change.
To determine whether PEJC were present under the baseline and whether they were mitigated,
exacerbated, or created by Option 3, EPA modeled baseline annual average PM2.5 concentrations and
concentration changes across various population groups of concern. Table 16 presents the results. It is
organized in the same way as Table 14, with rows for population groups and columns for areas, air quality
scenarios, and methods.31 A blue color gradient is applied to columns presenting total exposure burden
and a gray gradient is applied to columns presenting the absolute or relative change in exposure when
moving from the baseline to Option 3.
31 Numbers in Table 16 extend two and three places beyond the decimal point due to the small magnitude of air
quality changes; this is not intended to convey confidence in EPA's ability to estimate air quality exposures to
that level of exactness.
50
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Section 9—Distributional Analysis of Pollutant Exposures
Table 16. Modeled Average Annual PM2 5 Concentrations (ng/m3) Across Area Categories and Selected Population Groups in 2030
Population
Groups
Population (Ages)
1. Contiguous U.S.
Baseline
2. Contiguous U.S.
Policy
3. Changes in
Contiguous U.S.
4, % Change in
Contiguous U.S.
5. Baseline Areas
Changing
6. Policy Areas
Changing
7. Changes in Policy
Areas Changing
8, % Changes in
Changing Areas
9, Baseline Areas
Improving
10. Policy Areas
Improving
11. Changes in
Improving Areas
12. % Changes in
Improving Areas
13. Baseline Areas
Worsening
14. Policy Areas
Worsening
15. Changes in
Worsening Areas
16. % Changes in
Worsening Areas
17. Areas Not
Changing
Reference
Reference (0-99)
7.23
7.23
0.001
0.017
7.10
7.03
0.002
0.030
6.38
6.38
0.003
0.042
7.74
7.74
-0.002
-0.025
7.38
Race
White (0-99)
7.14
7.14
0.001
0.016
7.00
7.00
0.002
0.031
6.87
6.87
0.003
0.043
7.68
7.68
-0.002
-0.025
7.28
American Indian (0-99)
6.75
6.75
0.000
0.005
7.01
7.01
0.001
0.017
6.34
6.33
0.003
0.033
7.15
7.15
-0.002
-0.025
6.63
Asian (0-99)
7.80
7.80
0.001
0.011
7.42
7.42
0.002
0.024
7.27
7.27
0.003
0.036
8.16
8.16
-0.002
-0.023
8.10
Black (0-99)
7.43
7.48
0.002
0.023
7.37
7.37
0.002
0.032
7.30
7.30
0.003
0.040
7.86
7.36
-0.002
-0.025
7.75
Ethnicity
Non-Hispanic (0-99)
7.01
7.01
0.001
0.020
7.02
7.02
0.002
0.033
6.35
6.85
0.003
0.042
7.58
7.58
-0.002
-0.026
6.38
Hispanic (0-99)
8.02
8.02
0.001
0.007
7.42
7.41
0.001
0.018
7.15
7.15
0.003
0.038
8.02
8.02
-0.002
-0.024
8.47
Educational
Attainment
More educated (>24: HS or more)
7.13
7.13
0.001
0.018
7.05
7.05
0.002
0.032
6.35
6.85
0.003
0.042
7.70
7.70
-0.002
-0.025
7.22
Less educated (>24; no HS)
7.57
7.57
0.001
0.014
7.17
7.17
0.002
0.027
7.01
7.01
0.003
0.041
7.86
7.86
-0.002
-0.025
7.33
Poverty
Status
>200X of the poverty line (0-99)
7.16
7.16
0.001
0.017
7.07
7.07
0.002
0.031
6.35
6.35
0.003
0.041
7.72
7.72
-0.002
-0.025
7.27
<200X of the poverty line (0-99)
7.37
7.37
0.001
0.016
7.15
7.15
0.002
0.030
7.03
7.03
0.003
0.042
7.78
7.78
-0.002
-0.025
7.61
> Poverty line (0-99)
7.20
7.20
0.001
0.017
7.08
7.08
0.002
0.030
6.36
6.36
0.003
0.042
7.73
7.73
-0.002
-0.025
7.33
< Poverty line (0-99)
7.40
7.40
0.001
0.016
7.18
7.18
0.002
0.030
7.07
7.07
0.003
0.041
7.81
7.81
-0.002
-0.025
7.65
Linguistic
Isolation
English "very well or better" (0-99)
7.15
7.15
0.001
0.018
7.06
7.06
0.002
0.031
6.36
6.85
0.003
0.042
7.68
7.68
-0.002
-0.025
7.25
English < "very well" (0-99)
8.06
8.06
0.001
0.003
7.48
7.48
0.001
0.020
7.28
7.28
0.003
0.036
8.13
8.14
-0.002
-0.025
8.58
English "well or better" (0-99)
7.13
7.13
0.001
0.017
7.08
7.07
0.002
0.031
6.37
6.36
0.003
0.042
7.71
7.71
-0.002
-0.025
7.31
English < "well" (0-99)
CO
CO
8.18
0.001
0.003
7.54
7.54
0.001
0.013
7.33
7.33
0.003
0.035
8.17
8.17
-0.002
-0.025
8.75
Age
Children (0-17)
7.30
7.30
0.001
0.015
7.14
7.14
0.002
0.023
7.02
7.02
0.003
0.041
7.74
7.74
-0.002
-0.025
7.46
Adults (18-64)
7.28
7.28
0.001
0.016
7.14
7.13
0.002
0.030
7.02
7.01
0.003
0.041
7.78
7.78
-0.002
-0.025
7.44
Older Adults (65-99)
7.02
7.02
0.001
0.019
6.83
6.33
0.002
0.034
6.84
6.83
0.003
0.043
7.58
7.58
-0.002
-0.026
7.12
SeH
Females (0-99)
7.24
7.24
0.001
0.017
7.10
7.10
0.002
0.030
6.38
6.33
0.003
0.041
7.74
7.75
-0.002
-0.025
7.33
Males (0-99)
7.22
7.22
0.001
0.017
7.08
7.08
0.002
0.030
6.37
6.86
0.003
0.042
7.74
7.74
-0.002
-0.025
7.36
Note: Additional information on the column headers can be found in Table 15.
51
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Section 9—Distributional Analysis of Pollutant Exposures
Based on the results of the analysis, EPA determined that Option 3 would lead to small average annual
PM2.5 concentration improvements. Average total annual PM2.5 concentrations across the entire
contiguous U.S. under the baseline and Option 3 (columns 1 and 2 in Table 16) are similar when averaged
across the lower 48 states. The absolute magnitude of these changes is about 0.001-0.002 |ag/m3, less
than a 0.02 percent change from baseline concentrations, as shown in the first and second gray-shaded
columns in Table 16. Columns 5-8 in the table show average annual PM2.5 concentrations in areas with
predicted changes under Option 3, which includes both areas in which average annual PM2.5
concentrations improve (columns 9-12) or worsen (columns 13-16).32 Column 17 shows average annual
PM2.5 concentrations by population group in areas not affected by Option 3.
Because average annual PM2.5 concentrations in the baseline for Option 3 are similar to those in other
recent rulemakings (e.g., the RIA for the Reconsideration of the NAAQS for PM) and areas changing can
be more meaningfully discussed by directly considering improving and worsening areas, columns 1-8 in
Table 16 are not discussed in detail here.
As with MDA8 ozone concentrations, EPA found that there are differences in baseline average annual
PM2.5 exposures across population groups and area categories (Table 16). Also, as with MDA8 ozone,
absolute and relative changes in average annual PM2.5 exposures across population groups in improving
and worsening areas are similar (columns 11-12 and 15-16 in Table 16). This suggests that average annual
PM2.5 exposure disparities are not created, exacerbated, or mitigated under Option 3 compared to the
baseline.
To further evaluate distributional impacts, EPA evaluated differences in average annual PM2.5 exposures
between the various population groups of concern and their relevant comparison groups. Figure 7
presents the results. Colored lines to the right and left of the black line of total exposure distributions
(columns 1, 2, 4, 5, 7, 8, 10, 11, and 13) indicate disproportionately high and low exposures in the
population group of concern compared to the comparison group. Colored lines to the right and left of the
black line of exposure changes (columns 3, 6, 9, and 12 in ) indicate disproportionately large and small
exposure reductions in the population group of concerns compared to the comparison group.
3Z In other distributional and benefits assessments, air quality improvements have been shown as positive
numbers. In keeping with this precedent, worsening air quality concentrations are presented as negative
numbers here.
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Section 9—Distributional Analysis of Pollutant Exposures
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Section 9—Distributional Analysis of Pollutant Exposures
9.1.4 Key Conclusions
The results of EPA's distributional analysis of air quality impacts indicates that, under the baseline,
average annual PM2.5 and MDA8 ozone exposures are differentially higher among certain population
groups of concern relative to their relevant comparison groups (columns 1, 4, 7, 10, and 13 in Figure 4
and Figure 7). While the regulatory analysis estimating changes in average annual PM2.5 and MDA8 ozone
exposures shows increases and decreases in pollutant emissions across regions of the U.S. under Option
3, these changes overall are small and do not change the distribution of air quality impacts observed
under the baseline. Therefore, EPA concludes that the air quality changes resulting from Option 3 are not
expected to mitigate or exacerbate distributional disparities present under the baseline.
9.2 Surface Water
In addition to air emissions, EPA evaluated the distribution of pollutant loadings and the environmental
and human health effects of wastewater discharges from steam electric power plants into surface waters.
EPA analyzed these impacts in the immediate and downstream reaches of surface waters receiving
wastewater discharges. The following sections provide an overview of EPA's methodology for quantifying
these impacts and discuss the distribution of these impacts among all affected communities.
9.2.1 Immediate Receiving Waters
The term "immediate receiving water" is used to describe a reach of a surface water where a discharge of
wastewater occurs.33 To evaluate impacts within immediate receiving waters, EPA used the Immediate
Receiving Water (IRW) Model which quantitatively assesses potential water quality, wildlife, and human
health impacts from estimated pollutant loadings from steam electric power plant discharges.
The IRW Model evaluates water quality impacts by calculating annual average total and dissolved
pollutant concentrations34 in the water column and sediment of immediate receiving waters. It then
compares these concentrations to specific water quality criteria values-National Recommended Water
Quality Criteria (NRWQC) and MCLs-to assess potential impacts to wildlife and human health. To evaluate
potential impacts to wildlife, the model uses the annual average pollutant concentrations in the
immediate receiving water to estimate bioaccumulation of pollutants in fish tissue of trophic level35 3 (T3)
and trophic level 4 (T4) fish36. The model then compares these results to benchmark values-threshold
effect concentration (TEC) and no effect hazard concentration (NEHC)-to evaluate potential impacts on
exposed sediment biota and piscivorous wildlife37 that consume T3 and T4 fish, respectively. Estimated
fish tissue concentrations are also used to assess human health impacts-non-cancer and cancer risks38-to
33, The length of the immediate receiving water, as defined in the National Hydrography Dataset Plus (NHDPIus)
Version 2. See the 2023 EA for more details.
34 The pollutants modeled were arsenic, cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc.
35, A trophic level is a sequential stage in a food chain, i.e., producers (Tl), primary consumers (T2), secondary
consumers (T3), tertiary consumers (T4), and quaternary consumers (T5).
36, T3 fish {e.g., carp, smelt, perch, catfish, sucker, bullhead, sauger) are those that primarily consume
invertebrates and plankton, while T4 fish {e.g., salmon, trout, walleye, bass) are those that primarily consume
other fish (U.S. EPA, 2020).
37, The IRW Model uses minks and eagles to represent impacts to piscivorous wildlife because they live in most of
the United Sates and their diets primarily consist of T3 and T4 fish, respectively. Referencing a 2008 U.S.
Geological Survey (USGS) study Environmental Contaminants in Freshwater Fish and Their Risk to Piscivorous
Wildlife Based on a National Monitoring Program, the 2015 EA states that, "Minks and eagles are commonly
used in ecological risk assessments as indicator species for potential impacts to fish-eating mammals and birds
in areas contaminated with bioaccumulative pollutants (USGS, 2008)."
38, Non-cancer risks are evaluated for all pollutants based on a reference dose (RfD) that represents a dose that is
in general protective of human health, as opposed to a dose associated with a specific health endpoint. Cancer
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Section 9—Distributional Analysis of Pollutant Exposures
human populations from consuming fish that are caught in contaminated receiving waters. For a more
detailed discussion of the IRW Model see the 2023 EA.
EPA used the IRW Model to evaluate these impacts from steam electric power plant discharges for 98
immediate receiving waters receiving pollutant loadings from 85 plants. The results of the analyses are
presented under baseline conditions and for each of the regulatory options being considered for the
proposed rule. Information on the socioeconomic characteristics39 of affected communities is included
with the results from the model to evaluate the distribution of impacts (relative to the baseline) under
each of the regulatory options.
9.2.1.1 Distribution of Water Quality Impacts
Using the IRW Model, EPA compared immediate-receiving-water-specific pollutant concentrations in the
water column and sediment to benchmark values for NRWQC and MCLs. The benchmarks used for each
pollutant were the freshwater acute NRWQC, freshwater chronic NRWQC, human health water and
organism NRWQC, human health organism only NRWQC, and drinking water MCL. The comparison of
pollutant concentrations to these benchmarks enabled EPA to evaluate the potential for adverse impacts
to wildlife and human health for each immediate receiving water. For more information on the
methodology EPA used to evaluate water quality impacts, see the 2023 EA.
Table 17 presents the results of the IRW Model's analysis of water quality impacts for immediate
receiving waters with pollutant loadings from steam electric power plants that fall under the scope of the
proposed rule. Under the baseline and regulatory options, the table shows the socioeconomic
characteristics of communities impacted by immediate receiving waters exceeding pollutant-specific
benchmark values, compared to the socioeconomic characteristics of communities impacted by
immediate receiving waters without exceedances. This was done to assess whether, under the baseline,
communities impacted by immediate receiving waters with pollutant-specific benchmark exceedances
have larger populations of low-income individuals and racial and ethnic minorities than impacted
communities where immediate receiving waters do not have exceedances, and whether this distribution
of impacts changes under the regulatory options.
risks are calculated only for arsenic, which has a cancer slope factor identified in EPA's Integrated Risk
Information System (IRIS). See Appendix E of the 2020 EA.
39, To analyze the socioeconomic characteristics of communities expected to be impacted by pollutant loadings in
immediate receiving waters of steam electric power plants, EPA used the five-year (2015 to 2019) population
estimates from the U.S. Census Bureau's ACS dataset. EPA evaluated the percent of the affected population
that is low-income, defined in the ACS as the percent of the population below the poverty threshold. EPA also
evaluated the demographic characteristic of impacted communities across minority racial and ethnic categories
included in the ACS data. These racial and ethnic categories include: African American (non-Hispanic); Asian
(non-Hispanic); Native Hawaiian/Pacific Islander (non-Hispanic); American Indian/Alaska Native (non-Hispanic);
Other non-Hispanic; Hispanic/Latino.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 17. Immediate Receiving Water Community Demographics by Water Quality Benchmark Exceedances3 under the Baseline and Regulatory Options
National
Average
Baseline
Option 1
Option 2
Options 3 and 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Percent Low-Income
13.7%
5.4%
5.9%
5.3%
5.9%
5.3%
5.9%
6.4%
5.6%
Percent African
American (non-
12.2%
10.7%
6.1%
10.5%
6.7%
10.5%
6.7%
8.5%
7.5%
Hispanic)
Percent American
Indian/Alaska Native
0.7%
2.3%
0.8%
3.0%
0.7%
3.0%
0.7%
0.5%
1.4%
Percent Asian
5.4%
4.3%
0.9%
5.1%
0.9%
5.1%
0.9%
1.2%
2.2%
Percent Native
Hawaiian/Pacific
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Islander
Percent Other (non-
Hispanic)
2.7%
2.5%
2.4%
2.8%
2.3%
2.8%
2.3%
2.1%
2.5%
Percent
Hispanic/Latino
18.8%
8.7%
4.1%
10.3%
4.0%
10.3%
4.0%
6.8%
5.4%
Total Population
89,401
178,257
69,014
198,644
69,014
198,644
41,318
226,340
Count of IRW
34
64
25
73
24
74
19
79
Source: 2023 EA.
Abbreviations: IRW (immediate receiving water).
a - EPA compared pollutant concentrations in the receiving water attributed to steam electric power plant discharges to pollutant-specific water quality benchmarks to determine exceedances. Evaluated benchmarks include freshwater
acute, freshwater chronic, human health water and organism, and human health organism only National Recommended Water Quality Criteria (NRWQC); and drinking water maximum contaminant levels (MCLs). Evaluated pollutants
include arsenic, cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc. See the 2023 EA for more details on the analysis.
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Section 9—Distributional Analysis of Pollutant Exposures
Under the baseline, in general, the percent of the population identified as low-income or a racial and
ethnic minority population group is less than the national average in communities with immediate
receiving waters with and without pollutant-specific benchmark exceedances (Table 17). The one
exception occurs in communities with immediate receiving waters with exceedances, where the percent
of the population identified as American Indian or Alaska Native (non-Hispanic) is largerthan the national
average (Table 17). This result is driven by baseline exceedances observed in the Unnamed tributary to
the Chaco River, which is located in the Navajo Nation, an area in which about 98 percent of the
population is identified as American Indian or Alaska Native (non-Hispanic). Comparing the percent of the
population identified as low-income or a racial and ethnic minority population group between
communities with immediate receiving waters with and without exceedances, the results of the baseline
analysis show that communities with immediate receiving waters with exceedances have a larger
proportion of the population that is African-American (non-Hispanic), American Indian or Alaska Native
(non-Hispanic), Asian (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino (Table 17). Although,
when comparing the populations identified as low-income or a racial ethnic minority population group in
absolute terms, the number of people in these groups is higher in communities with immediate receiving
waters without exceedances, except for the American Indian or Alaska Native (non-Hispanic) Asian (non-
Hispanic), and Hispanic or Latino population groups (Table 17). This is due to the fact that, under the
baseline, the majority of immediate receiving waters do not have exceedances and the majority of the
affected population lives in those areas (Table 17).
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with pollutant-specific benchmark exceedances and the population affected by these
exceedances compared to the baseline. Options 3 and 4 generate the largest reductions (Table 17).
Under Options 1 and 2, as in the baseline, the percent of the population identified as low-income or a
racial and ethnic minority population group is less than the national average, except for those identified
as American Indian or Alaska Native (non-Hispanic) in communities with immediate receiving waters with
exceedances (Table 17). When comparing between communities with immediate receiving waters with
and without exceedances, under Options 1 and 2, as in the baseline, the percent of the population
identified as low-income or a racial and ethnic minority population group is larger in communities with
immediate receiving waters with exceedances for African-American (non-Hispanic), American Indian or
Alaska Native (non-Hispanic), Asian (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino
(Table 17). Under Options 1 and 2, increases in the precent of the population identifying as American
Indian or Alaska Native (non-Hispanic), Asian (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino
were observed relative to the baseline (Table 17). While these increases were observed, it is important to
note that under Options 1 and 2 the number of immediate receiving waters with exceedances and the
proportion of the total affected population living in those areas decreases compared to the baseline
(Table 17). Therefore, the increases in the percent of the population belongingto these groups is not due
to an increase in immediate receiving water with exceedances, but rather that the remaining immediate
receiving waters with exceedances under Options 1 and 2 have smaller populations with greater
proportions of these racial and ethnic minority groups than the immediate receiving waters without
exceedances.
Under Options 3 and 4, the percent of the population identified as low-income or a racial and ethnic
minority population groups is less than the national average in communities with immediate receiving
waters with and without exceedances compared to the baseline (Table 17). As opposed to Options 1 and
2, this includes the percent of the populations that identifies as American Indian and Alaska Native (non-
Hispanic) in communities with immediate receiving waters with exceedances, as the Unnamed tributary
to the Chaco River would no longer have exceedances (Table 17). When comparing between communities
with immediate receiving waters with and without exceedances, under Options 3 and 4, communities
with immediate receiving waters with exceedances had a larger percent of the population identifying as
low-income, African-American (non-Hispanic), and Hispanic/Latino than communities with immediate
receiving waters without exceedances (Table 17). Under Options 3 and 4, in particular with the percent of
the population identifying as low-income in communities with immediate receiving waters with
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Section 9—Distributional Analysis of Pollutant Exposures
exceedances, an increase was observed compared to the baseline (Table 17). Given that, in absolute
terms, Options 3 and 4 generate the greatest reductions in the number of immediate receiving waters
with exceedances and the population living in those areas compared to the baseline, this increase is likely
the result of the remaining immediate receiving waters with exceedances having smaller populations with
greater proportions of low-income people (Table 17). Across all racial and ethnic groups analyzed,
Options 3 and 4 result in a decrease in the percent of the population in those groups compared to the
baseline (Table 17).
9.2.1.1.1 Key Conclusions
Based on the results of the analysis, EPA found evidence of PEJC under the baseline among affected
American Indian or Alaska Native (non-Hispanic) populations when comparing the percent of the
population affected to the national average. Making an internal comparison among the affected
population, EPA found PEJC among African-American (non-Hispanic), American Indian or Alaska Native
(non-Hispanic), Asian (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino populations as they
comprised a larger proportion of the population in communities with immediate receiving waters with
exceedances than in communities with immediate receiving waters without exceedances. Analyzing the
regulatory options, EPA found that all regulatory options resulted in a reduction in the number of
immediate receiving waters with exceedances and the populations affected by those exceedances
compared to the baseline. EPA concluded the Options 3 and 4 generated the largest reductions in
immediate receiving waters with exceedances and the population affected by the exceedances. EPA also
concluded that Options 3 and 4 produced the greatest improvements in the distribution of impacts across
the population groups of concern relative to the baseline.
9.2.1.1.2 Distribution of Wildlife Impacts
Once the water quality impacts were assessed, EPA used the IRW Model to evaluate potential wildlife
impacts in immediate receiving waters. The IRW Model performs two types of analyses to evaluate
potential wildlife impacts. The first is an analysis that compares pollution concentration in sediment of
immediate receiving waters to TECs for sediment biota. For the second analysis, the IRW Model calculates
the bioaccumulation of pollutants in T3 and T4 fish tissue and compares the fish tissue concentrations to
NEHCs for minks and eagles. EPA uses the results of the two analyses to evaluate potential impacts on
wildlife from pollutant discharges to the immediate receiving waters. For more information on the
methodology EPA used to evaluate wildlife impacts see the 2023 EA and Appendix D of the 2020 EA.
The following tables present the results of the analyses on impacts to sediment biota, mink, and eagles.
Table 18-20 present the socioeconomic characteristics of communities with immediate receiving waters
with and without sediment pollutant concentrations that exceed the TEC for sediment biota, fish tissue
concentrations that exceed the NEHC for mink, and fish tissue concentrations that exceed the NEHC for
eagles, respectively, under the baseline and regulatory options. This was done to assess whether, under
the baseline, communities impacted by immediate receiving waters with TEC and NEHC exceedances
have larger populations of low-income people and racial and ethnic minorities than impacted
communities where immediate receiving waters do not have exceedances, and whether this distribution
of impacts changes under the regulatory options.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 18. Immediate Receiving Water Community Demographics by Sediment Benchmark Exceedances3 under
Baseline and the Regulatory Options
Baseline
Options 1 and 2
Options 3 and 4
Demographics
National
Average
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Percent Low-Income
13.7%
7.0%
5.5%
7.0%
5.5%
6.7%
5.6%
Percent African American (non-
Hispanic)
12.2%
8.9%
7.4%
8.9%
7.4%
9.3%
7.4%
Percent American Indian/Alaska
Native
0.7%
4.4%
0.8%
4.4%
0.8%
0.2%
1.5%
Percent Asian
5.4%
1.2%
2.1%
1.2%
2.1%
1.2%
2.1%
Percent Native Hawaiian/Pacific
Islander
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-Hispanic)
2.7%
2.2%
2.5%
2.2%
2.5%
2.3%
2.4%
Percent Hispanic/Latino
18.8%
5.3%
5.7%
5.3%
5.7%
5.5%
5.6%
Total Population
38,124
229,534
38,124
229,534
36,477
231,181
Count of IRW
19
79
19
79
18
80
Source: 2023 EA
Abbreviations: IRW (immediate receiving water).
a - EPA compared pollutant concentrations in the receiving water sediment attributed to steam electric power plant discharges to pollutant-specific threshold effect
concentrations (TECs) for sediment biota to determine exceedances. Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc. See the
2023 EAfor more details on the analysis.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 19. Immediate Receiving Water Community Demographics by NEHC Exceedances3 for Eagles (Ingesting T4 Fish)
under Baseline and the Regulatory Options
National
Average
Baseline
Options 1 and 2
Options 3 and 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Percent Low-Income
13.7%
6.9%
5.5%
6.9%
5.6%
6.5%
5.6%
Percent African American
(non-Hispanic)
12.2%
9.9%
7.3%
10.1%
7.3%
10.6%
7.3%
Percent American
Indian/Alaska Native
0.7%
4.9%
0.8%
5.2%
0.8%
0.2%
1.5%
Percent Asian
5.4%
1.3%
2.1%
1.3%
2.1%
1.3%
2.1%
Percent Native
Hawaiian/Pacific Islander
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-Hispanic)
2.7%
2.4%
2.4%
2.5%
2.4%
2.6%
2.4%
Percent Hispanic/Latino
18.8%
5.9%
5.6%
6.2%
5.5%
6.4%
5.5%
Total Population
34,461
233,197
32,392
235,266
30,745
236,913
Count of IRW
18
80
15
83
14
84
Source: 2023 EA
Abbreviations: IRW (immediate receiving water); T4 (trophic level 4).
a - EPA compared fish tissue concentrations (T4) in the receiving water attributed to steam electric power plant discharges to pollutant-specific no effect hazard concentrations
(NEHCs) for eagles (ingesting T4 fish) to determine exceedances. Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc. See the 2023
EA for more details on the analysis.
Note: EPA did not identify an NEHC value for methylmercury. EPA compared the modeled methylmercury concentrations to the total mercury NEHC, which may underestimate
the impact to wildlife.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 20. Immediate Receiving Water Community Demographics by NEHC Exceedances3 for Minks (Ingesting T3 Fish)
under Baseline and the Regulatory Options
Baseline
Options 1 and 2
Options 3 and 4
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Percent Low-Income
6.9%
5.6%
6.9%
5.6%
6.5%
5.6%
Percent African American (non-
Hispanic)
10.1%
7.3%
10.1%
7.3%
10.6%
7.3%
Percent American Indian/Alaska
Native
5.2%
0.8%
5.2%
0.8%
0.2%
1.5%
Percent Asian
1.3%
2.1%
1.3%
2.1%
1.3%
2.1%
Percent Native Hawaiian/Pacific
Islander
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-Hispanic)
2.5%
2.4%
2.5%
2.4%
2.6%
2.4%
Percent Hispanic/Latino
6.2%
5.5%
6.2%
5.5%
6.4%
5.5%
Total Population
32,392
235,266
32,392
235,266
30,745
236,913
Count of IRW
15
83
15
83
14
84
Source: 2023 EA
Abbreviations: IRW (immediate receiving water); T3 (trophic level 3).
a - EPA compared fish tissue concentrations (T3) in the receiving water attributed to steam electric power plant discharges to pollutant-specific no effect hazard concentrations
(NEHCs) for minks (ingesting T3 fish) to determine exceedances. Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc. See the 2023
EA for more details on the analysis.
Note: EPA did not identify an NEHC value for methylmercury. EPA compared the modeled methylmercury concentrations to the total mercury NEHC, which may underestimate
the impact to wildlife.
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Section 9—Distributional Analysis of Pollutant Exposures
Across the sediment biota, eagle, and mink wildlife analyses, under the baseline, the percent of the
population identified as low-income or a racial and ethnic minority population group is less than the
national average in communities with immediate receiving waters with and without pollutant-specific
benchmark exceedances (Tables 18-20). The one exception occurs in communities with immediate
receiving waters with and without exceedances, where the percent of the population identified as
American Indian or Alaska Native (non-Hispanic) is larger than the national average (Tables 18-20). This
result is driven by baseline exceedances observed in the Unnamed tributary to the Chaco River, which is
in the Navajo Nation, an area in which about 98 percent of the population identified as American Indian
or Alaska Native (non-Hispanic) (Tables 18-20). Across the three wildlife analyses, comparing the percent
of the population identified as low-income or a racial and ethnic minority population group between
communities with immediate receiving waters with and without exceedances, the results of the baseline
analysis show that communities with immediate receiving waters with exceedances have a larger
proportion of the population that is low-income, African-American (non-Hispanic), American Indian or
Alaska Native (non-Hispanic), Other (non-Hispanic), or Hispanic or Latino (Tables 18-20). Although, when
comparing the populations identified as low-income or a racial ethnic minority population group in
absolute terms, the number of people in these groups is higher in communities with immediate receiving
waters without exceedances across all the population groups of concern (Tables 18-20). This is due to the
fact that, across the three wildlife analyses, under the baseline, the majority of immediate receiving
waters do not have exceedances and the majority of the affected population lives in those areas
(Tables 18-20).
The results of the analysis of regulatory options show that none of the options increase the number of
immediate receiving waters with pollutant-specific benchmark exceedances for sediment biota, eagle,
and mink and the population affected by these exceedances compared to the baseline (Tables 18-20).
Additionally, Options 3 and 4 generate the greatest reduction in the number of immediate receiving
waters with exceedances and the population affected by these exceedances relative to the baseline
(Tables 18-20).
The results of the sediment biota and mink wildlife analyses show that Options 1 and 2 do not change the
number of immediate receiving waters with and without exceedances and the distribution of impacts
across the population groups of concern relative to the baseline (Table 18 and Table 20).
In the eagle wildlife analysis, under Options 1 and 2, as in the baseline, the percent of the population
identified as low-income or a racial and ethnic minority population group is less than the national
average, except for those identified as American Indian or Alaska Native (non-Hispanic) in communities
with immediate receiving waters with and without exceedances (Table 19). When comparing between
communities with immediate receiving waters with and without exceedances, under Options 1 and 2, the
percent of the population identified as low-income, African-American (non-Hispanic), American Indian or
Alaska Native (non-Hispanic), Other (non-Hispanic) and Hispanic or Latino is larger in communities with
immediate receiving waters with exceedances (Table 19). Under Options 1 and 2, small increases in the
precent of the population identifying as African-American (non-Hispanic), American Indian or Alaska
Native (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino were observed relative to the
baseline (Table 19). While these increases were observed, it is important to note that under Options 1
and 2 the number of immediate receiving waters with exceedances and the proportion of the total
affected population living in those areas decreases compared to the baseline (Table 19). Therefore, the
increases in the percent of the population belonging to these groups is not due to an increase in
immediate receiving water with exceedances, but rather that the remaining immediate receiving waters
with exceedances under Options 1 and 2 have smaller populations with greater proportions of these
population groups of concern than the immediate receiving waters without exceedances (Table 19).
Across the sediment biota, eagle, and mink wildlife analyses, under Options 3 and 4, the percent of the
population identified as low-income or a racial and ethnic minority population group is less than the
national average in communities with immediate receiving waters with exceedances compared to the
baseline (Tables 18-20). As opposed to Options 1 and 2, this includes the percent of the population that
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Section 9—Distributional Analysis of Pollutant Exposures
identifies as American Indian and Alaska Native (non-Hispanic) in communities with immediate receiving
waters with exceedances (Tables 18-20). This is likely due to the Unnamed tributary to the Chaco River,
no longer having exceedances under Options 3 and 4 compared to the baseline in all three analyses. The
results of the sediment biota and mink wildlife analysis show that, when comparing between
communities with immediate receiving waters with and without exceedances, under Options 3 and 4,
communities with immediate receiving waters with exceedances had a larger percent of the population
identifying as low-income and African-American (non-Hispanic) than communities with immediate
receiving waters without exceedances (Table 18 and Table 20). In the eagle wildlife analysis, under
Options 3 and 4, communities with immediate receiving waters with exceedances had a larger percent of
the population identifying as low-income, African-American (non-Hispanic), Other (non-Hispanic), and
Hispanic or Latino than communities with immediate receiving waters without exceedances (Table 19).
Under Options 3 and 4, in particular with the percent of the population identifying as African-American
(non-Hispanic), Other (non-Hispanic), and Hispanic or Latino in communities with immediate receiving
waters with exceedances, small increases were observed compared to the baseline (Table 19).
Furthermore, the results of the mink wildlife analysis show that, in communities with immediate receiving
waters with exceedances, populations identified as African-American (non-Hispanic), Other (non-
Hispanic), and Hispanic or Latino had small increases in their proportion of the affected population under
Options 3 and 4 compared to the baseline (Table 20). Given that across the three wildlife analyses, in
absolute terms, Options 3 and 4 generate the greatest reductions in the number of immediate receiving
waters with exceedances and the population living in those areas compared to the baseline, the increases
observed in the eagle and mink wildlife analyses are likely the result of the remaining immediate receiving
waters with exceedances having smaller populations with greater proportions of these population groups
of concern (Table 19 and Table 20).
9.2.1.1.3 Key Conclusions
Based on the results of the distributional analysis of wildlife impacts, across the three analyses, EPA found
that under the baseline PEJC were observed only among affected American Indian or Alaska Native (non-
Hispanic) populations when comparing the percent of the population affected in communities with
immediate receiving waters with pollutant-specific benchmark exceedances to the national average.
Making an internal comparison between the affected population, EPA found PEJC among specific
population groups of concern as they comprised a larger proportion of the population in communities
with immediate receiving waters with exceedances than in communities with immediate receiving waters
without exceedances. Analyzing the regulatory options across the three analyses, EPA found that Options
3 and 4 consistently generated the largest reductions in immediate receiving waters with exceedances
and the population affected by the exceedances. EPA also concluded that Options 3 and 4 consistently
produced the greatest improvements in the distribution of impacts across the population groups of
concern relative to the baseline.
9.2.1.1.4 Distribution of Human Health Impacts
After impacts to wildlife were evaluated, EPA used the fish tissue concentrations calculated by the IRW
Model to assess non-cancer and cancer risks to human populations from consuming fish caught in
contaminated immediate receiving waters. Non-cancer and cancer risks are calculated for four human
cohorts: child recreational, adult recreational, child subsistence, and adult subsistence. For more
information on the methodology EPA used to evaluate human health impacts, see the 2023 EA and
Appendix E of the 2020 EA.
Non-cancer human health risks are evaluated by comparing the cohort- and pollutant-specific daily intake
of a pollutant from fish ingestion-expressed as an average daily dose (mg/kg/day)-to cohort- and
pollutant-specific oral reference doses (RfDs). Based on these factors, in each cohort, a hazard quotient
(HQ) value is calculated for each immediate receiving water by dividing the average daily dose by the
RfDs. If an immediate receiving water has an HQ greater than one (1.0), EPA identifies it as having an
exceedance of a non-cancer human health risk.
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Section 9—Distributional Analysis of Pollutant Exposures
EPA evaluated cancer human health risks from arsenic by estimating a lifetime average daily dose (LADD)
and a corresponding lifetime excess cancer risk (LECR) for each cohort. EPA then compared the LECR to a
benchmark of one-in-a-million (1.00 x 10-6). LECRs are calculated for each immediate receiving water. If
an immediate receiving water has an LECR greater than 1.00 x 10-6, EPA identified it as having an LECR
exceedance.
Table 21 and Table 22 show the results from the EJ analysis of the IRW Model's estimated non-cancer and
cancer health impacts under the baseline and regulatory options for each cohort. This was done to
determine whether, for each cohort, communities with immediate receiving waters with exceedances
have a larger proportion of population groups of concern.
Table 21 presents the socioeconomic characteristics of communities with immediate receiving waters
with and without HQs greater than one.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 21. Immediate Receiving Water Community Demographics by Oral RfD Exceedances3 under Baseline and the Regulatory Options, Organized by Age and Fishing Mode Cohort
Baseline
Option 1
Option 2
Options 3 and 4
Demographics
National Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Child, Recreational Fisher
Percent Low-Income
13.7%
6.9%
5.4%
7.0%
5.5%
7.0%
5.5%
6.6%
5.6%
Percent African American
(non-Hispanic)
12.2%
9.6%
7.2%
9.7%
7.3%
9.9%
7.3%
10.6%
7.3%
Percent American
Indian/Alaska Native
0.7%
3.3%
0.8%
4.8%
0.8%
4.9%
0.8%
0.2%
1.5%
Percent Asian
5.4%
0.9%
2.3%
1.3%
2.1%
1.2%
2.1%
1.3%
2.1%
Percent Native
Hawaiian/Pacific Islander
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-Hispanic)
2.7%
1.8%
2.6%
2.4%
2.4%
2.4%
2.4%
2.5%
2.4%
Percent Hispanic/Latino
18.8%
5.8%
5.6%
5.8%
5.6%
5.9%
5.6%
6.2%
5.5%
Total Population
56,069
211,589
35,026
232,632
34,296
233,362
32,084
235,574
Count of IRW
28
70
19
79
18
80
16
82
Adult, Recreational Fisher
Percent Low-Income
13.7%
7.4%
5.4%
7.1%
5.5%
7.1%
5.5%
6.6%
5.6%
Percent African American
(non-Hispanic)
12.2%
9.1%
7.4%
10.7%
7.3%
10.7%
7.3%
11.4%
7.2%
Percent American
Indian/Alaska Native
0.7%
4.0%
0.8%
5.5%
0.8%
5.5%
0.8%
0.2%
1.4%
Percent Asian
5.4%
1.1%
2.2%
1.4%
2.1%
1.4%
2.1%
1.5%
2.1%
Percent Native
Hawaiian/Pacific Islander
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-Hispanic)
2.7%
2.1%
2.5%
2.6%
2.4%
2.6%
2.4%
2.8%
2.4%
Percent Hispanic/Latino
18.8%
4.9%
5.8%
5.9%
5.6%
5.9%
5.6%
6.2%
5.6%
Total Population
42,822
224,836
30,722
236,936
30,722
236,936
28,510
239,148
Count of IRW
23
75
15
83
15
83
13
85
Child, Subsistence Fisher
Percent Low-Income
13.7%
5.2%
6.0%
5.6%
5.8%
5.6%
5.8%
7.1%
5.5%
Percent African American
(non-Hispanic)
12.2%
11.0%
5.9%
12.2%
6.4%
12.2%
6.4%
9.6%
7.3%
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Section 9—Distributional Analysis of Pollutant Exposures
Table 21. Immediate Receiving Water Community Demographics by Oral RfD Exceedances3 under Baseline and the Regulatory Options, Organized by Age and Fishing Mode Cohort
Baseline
Option 1
Option 2
Options 3 and 4
Demographics
National Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Percent American
Indian/Alaska Native
0.7%
2.1%
0.9%
2.9%
0.9%
2.9%
0.9%
0.3%
1.5%
Percent Asian
5.4%
4.1%
0.9%
5.6%
1.0%
5.6%
1.0%
1.2%
2.2%
Percent Native
Hawaiian/Pacific Islander
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.2%
0.1%
Percent Other (non-Hispanic)
2.7%
2.5%
2.4%
2.9%
2.3%
2.9%
2.3%
2.1%
2.5%
Percent Hispanic/Latino
18.8%
8.4%
4.2%
9.6%
4.5%
9.6%
4.5%
5.1%
5.7%
Total Population
90,571
177,087
58,580
209,078
58,580
209,078
40,610
227,048
Count of IRW
35
63
25
73
24
74
21
77
Adult, Subsistence Fisher
Percent Low-Income
13.7%
6.9%
5.4%
7.0%
5.5%
7.0%
5.5%
6.5%
5.6%
Percent African American
(non-Hispanic)
12.2%
9.6%
7.2%
9.7%
7.3%
9.7%
7.3%
10.3%
7.3%
Percent American
Indian/Alaska Native
0.7%
3.3%
0.8%
4.8%
0.8%
4.8%
0.8%
0.2%
1.5%
Percent Asian
5.4%
0.9%
2.3%
1.3%
2.1%
1.3%
2.1%
1.4%
2.1%
Percent Native
Hawaiian/Pacific Islander
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-Hispanic)
2.7%
1.8%
2.6%
2.4%
2.4%
2.4%
2.4%
2.5%
2.4%
Percent Hispanic/Latino
18.8%
5.8%
5.6%
5.8%
5.6%
5.8%
5.6%
6.1%
5.6%
Total Population
56,069
211,589
35,026
232,632
35,026
232,632
32,814
234,844
Count of IRW
28
70
19
79
19
79
17
81
Source: 2023 EA
Abbreviations: IRW (immediate receiving water); RfD (reference dose).
a - EPA compared the human health cohort's daily intake of a pollutant from ingesting fish from the receiving water to pollutant-specific oral reference doses (RfDs) to determine exceedances. Evaluated pollutants include arsenic
(inorganic), cadmium, copper, mercury (as methylmercury), nickel, selenium, and zinc. See the 2023 EAfor more details on the analysis.
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Section 9—Distributional Analysis of Pollutant Exposures
Child Recreational Consumption
Under the baseline, in general, the percent of the population identified as low-income or a racial and
ethnic minority population group is less than the national average in communities with immediate
receiving waters with and without non-cancer HQs greater than one (Table 21). The one exception occurs
in communities with immediate receiving waters with and without exceedances, where the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) is larger than the national
average (Table 21). Comparing the percent of the population identified as low-income or a racial and
ethnic minority population group between communities with immediate receiving waters with and
without exceedances, the results of the baseline analysis show that communities with immediate
receiving waters with exceedances have a larger proportion of the population that is low-income, African-
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), and Hispanic or Latino
(Table 21). Although, when comparing the populations identified as low-income or a racial ethnic minority
population group in absolute terms, the number of people in these groups is higher in communities with
immediate receiving waters without exceedances across all the population groups of concern (Table 21).
This is due to the fact that, under the baseline, the majority of immediate receiving waters do not have
exceedances and the majority of the affected population lives in those areas (Table 21).
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the population affected by these HQ
exceedances compared to the baseline (Table 21). Options 3 and 4 generate the largest reductions
(Table 21).
Under Options 1 and 2, as in the baseline, the percent of the population identified as low-income or a
racial and ethnic minority population group is less than the national average, except for those identified
as American Indian or Alaska Native (non-Hispanic) in communities with immediate receiving waters with
and without exceedances (Table 21). When comparing between communities with immediate receiving
waters with and without exceedances, under Options 1 and 2, the percent of the population identified as
low-income, African-American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), and
Hispanic or Latino is larger in communities with immediate receiving waters with exceedances (Table 21).
Under Options 1 and 2, small increases in the proportion of the population identifying as these population
groups of concern and Asian (non-Hispanic) and Other (non-Hispanic) populations were observed relative
to the baseline (Table 21). It is important to note that under Options 1 and 2 the number of immediate
receiving waters with exceedances and the proportion of the total affected population living in those
areas decreases compared to the baseline (Table 21). Therefore, the increases in the percent of the
population belonging to these groups is not due to an increase in immediate receiving water with
exceedances, but rather that the remaining immediate receiving waters with exceedances under Options
1 and 2 have smaller populations with greater proportions of these population groups of concern than
the immediate receiving waters without exceedances (Table 21).
Under Options 3 and 4, in general, the percent of the population identified as low-income or a racial and
ethnic minority population groups is less than the national average in communities with immediate
receiving waters with and without exceedances compared to the baseline (Table 21). As opposed to
Options 1 and 2, this includes the percent of the population that identifies as American Indian and Alaska
Native (non-Hispanic) in communities with immediate receiving waters with exceedances (Table 21). This
change is likely due to Options 3 and 4 removing exceedances for the Unnamed tributary to the Chaco
River which is in a tribal area. When comparing between communities with immediate receiving waters
with and without exceedances, under Options 3 and 4, communities with immediate receiving waters
with exceedances had a larger percent of the population identifying as low-income, African-American
(non-Hispanic), Other (non-Hispanic), and Hispanic or Latino than communities with immediate receiving
waters without exceedances (Table 21). Under Options 3 and 4, for these population groups of concern
and Asian (non-Hispanic) populations, small increases were observed compared to the baseline
(Table 21). Given that, in absolute terms, Options 3 and 4 generate the greatest reductions in the number
of immediate receiving waters with exceedances and the population living in those areas compared to the
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Section 9—Distributional Analysis of Pollutant Exposures
baseline, this increase is likely the result of the remaining immediate receiving waters with exceedances
having smaller populations with greater proportions of low-income, African-American (non-Hispanic),
Asian (non-Hispanic) Other (non-Hispanic) and Hispanic or Latino individuals (Table 21).
Adult Recreational Consumption
Under the baseline, in general, the percent of the population identified as low-income or a racial and
ethnic minority population group is less than the national average in communities with immediate
receiving waters with and without non-cancer HQs greater than one (Table 21). The one exception occurs
in communities with immediate receiving waters with and without exceedances, where the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) is larger than the national
average (Table 21). Comparing the percent of the population identified as low-income or a racial and
ethnic minority population group between communities with immediate receiving waters with and
without exceedances, the results of the baseline analysis show that communities with immediate
receiving waters with exceedances have a larger proportion of the population that is low-income, African-
American (non-Hispanic), and American Indian or Alaska Native (non-Hispanic) (Table 21). Although, when
comparing the populations identified as low-income or a racial ethnic minority population group in
absolute terms, the number of people in these groups is higher in communities with immediate receiving
waters without exceedances across all the population groups of concern (Table 21). This is due to the fact
that, under the baseline, the majority of immediate receiving waters do not have exceedances and the
majority of the affected population lives in those areas (Table 21).
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the population affected by these HQ
exceedances compared to the baseline (Table 21). Options 3 and 4 generate the largest reductions
(Table 21).
Under Options 1 and 2, as in the baseline, the percent of the population identified as low-income or a
racial and ethnic minority population group is less than the national average, except for those identified
as American Indian or Alaska Native (non-Hispanic) in communities with immediate receiving waters with
and without exceedances (Table 21). When comparing between communities with immediate receiving
waters with and without exceedances, under Options 1 and 2, the percent of the population identified as
low-income, African-American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), Asian
(non-Hispanic), and Hispanic or Latino is larger in communities with immediate receiving waters with
exceedances (Table 21). Under Options 1 and 2, for these population groups of concern, except low-
income populations, small increases in their proportion of the affected population were observed relative
to the baseline (Table 21). It is important to note that, again, the increases in the percent of the
population belonging to these groups is due to the remaining immediate receiving waters with
exceedances under Options 1 and 2 have smaller populations with greater proportions of these
population groups of concern (Table 21).
Under Options 3 and 4, in general, the percent of the population identified as low-income or a racial and
ethnic minority population groups is less than the national average in communities with immediate
receiving waters with and without exceedances compared to the baseline (Table 21). As opposed to
Options 1 and 2, this includes the percent of the population that identifies as American Indian and Alaska
Native (non-Hispanic) in communities with immediate receiving waters with exceedances (Table 21). This
change is likely due to Options 3 and 4 removing exceedances for the Unnamed tributary to the Chaco
River which is in a tribal area (Table 21). When comparing between communities with immediate
receiving waters with and without exceedances, under Options 3 and 4, communities with immediate
receiving waters with exceedances had a larger percent of the population identifying as low-income,
African-American (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino than communities with
immediate receiving waters without exceedances (Table 21). Under Options 3 and 4, for these population
groups of concern (except for low-income populations) and Asian (non-Hispanic) populations, small
increases in their proportion of the affected population were observed compared to the baseline
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Section 9—Distributional Analysis of Pollutant Exposures
(Table 21). This increase is likely the result of the remaining immediate receiving waters with exceedances
having smaller populations with greater proportions of these population groups of concern (Table 21).
Child Subsistence Consumption
Under the baseline, in general, the percent of the population identified as low-income or a racial and
ethnic minority population group is less than the national average in communities with immediate
receiving waters with and without non-cancer HQs greater than one (Table 21). The one exception occurs
in communities with immediate receiving waters with and without exceedances, where the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) is larger than the national
average (Table 21). Comparing the percent of the population identified as low-income or a racial and
ethnic minority population group between communities with immediate receiving waters with and
without exceedances, the results of the baseline analysis show that communities with immediate
receiving waters with exceedances have a larger proportion of the population that is African-American
(non-Hispanic), American Indian or Alaska Native (non-Hispanic), Asian (non-Hispanic), Other (non-
Hispanic), and Hispanic or Latino. (Table 21). Although, when comparing the populations identified as
low-income or a racial ethnic minority population group in absolute terms, the number of people in these
groups is higher in communities with immediate receiving waters without exceedances across all the
population groups of concern (Table 21). This is due to the fact that, under the baseline, the majority of
immediate receiving waters do not have exceedances and the majority of the affected population lives in
those areas (Table 21).
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the population affected by these HQ
exceedances compared to the baseline (Table 21). Options 3 and 4 generate the largest reductions
(Table 21).
Under Options 1 and 2, as in the baseline, the percent of the population identified as low-income or a
racial and ethnic minority population group is less than the national average, except for those identified
as American Indian or Alaska Native (non-Hispanic) in communities with immediate receiving waters with
and without exceedances (Table 21). When comparing between communities with immediate receiving
waters with and without exceedances, the percent of the population is larger in communities with
immediate receiving waters with exceedances for the same population groups of concern as in the
baseline (Table 21). Under Options 1 and 2, for these population groups of concern and low-income
populations small increases in their proportion of the affected population were observed relative to the
baseline (Table 21). This is due to the remaining immediate receiving waters with exceedances under
Options 1 and 2 having smaller populations with greater proportions of these population groups of
concern (Table 21).
Under Options 3 and 4, in general, the percent of the population identified as low-income or a racial and
ethnic minority population groups is less than the national average in communities with immediate
receiving waters with and without exceedances compared to the baseline (Table 21). As opposed to
Options 1 and 2, this includes the percent of the population that identifies as American Indian and Alaska
Native (non-Hispanic) in communities with immediate receiving waters with exceedances (Table 21). This
change is likely due to Options 3 and 4 removing exceedances for the Unnamed tributary to the Chaco
River which is in a tribal area. When comparing between communities with immediate receiving waters
with and without exceedances, under Options 3 and 4, communities with immediate receiving waters
with exceedances had a larger percent of the population identifying as low-income, African-American
(non-Hispanic), and Native Hawaiian or Pacific Islander (non-Hispanic) than communities with immediate
receiving waters without exceedances (Table 21). Under Options 3 and 4, for these population groups of
concern, small increases in their proportion of the affected population were observed compared to the
baseline (Table 21). This increase is likely the result of the remaining immediate receiving waters with
exceedances having smaller populations with greater proportions of these population groups of concern.
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Section 9—Distributional Analysis of Pollutant Exposures
Adult Subsistence Consumption
Under the baseline, in general, the percent of the population identified as low-income or a racial and
ethnic minority population group is less than the national average in communities with immediate
receiving waters with and without non-cancer HQs greater than one (Table 21). The one exception occurs
in communities with immediate receiving waters with and without exceedances, where the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) is largerthan the national
average (Table 21). Comparing the percent of the population identified as low-income or a racial and
ethnic minority population group between communities with immediate receiving waters with and
without exceedances, the results of the baseline analysis show that communities with immediate
receiving waters with exceedances have a larger proportion of the population that is low-income, African-
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), and Hispanic or Latino
(Table 21). Although, when comparing the populations identified as low-income or a racial ethnic minority
population group in absolute terms, the number of people in these groups is higher in communities with
immediate receiving waters without exceedances across all the population groups of concern (Table 21).
This is due to the fact that, under the baseline, the majority of immediate receiving waters do not have
exceedances and the majority of the affected population lives in those areas (Table 21).
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the population affected by these HQ
exceedances compared to the baseline (Table 21). Options 3 and 4 generate the largest reductions
(Table 21).
Under Options 1 and 2, as in the baseline, the percent of the population identified as low-income or a
racial and ethnic minority population group is less than the national average, except for those identified
as American Indian or Alaska Native (non-Hispanic) in communities with immediate receiving waters with
and without exceedances (Table 21). When comparing between communities with immediate receiving
waters with and without exceedances, the percent of the population is larger in communities with
immediate receiving waters with exceedances for the same population groups of concern as in the
baseline (Table 21). Under Options 1 and 2, for these population groups of concern, small increases in
their proportion of the affected population were observed relative to the baseline (Table 21). This is due
to the remaining immediate receiving waters with exceedances under Options 1 and 2 having smaller
populations with greater proportions of these population groups of concern (Table 21).
Under Options 3 and 4, in general, the percent of the population identified as low-income or a racial and
ethnic minority population groups is less than the national average in communities with immediate
receiving waters with and without exceedances compared to the baseline (Table 21). As opposed to
Options 1 and 2, this includes the percent of the population that identifies as American Indian and Alaska
Native (non-Hispanic) in communities with immediate receiving waters with exceedances (Table 21). This
change is likely due to Options 3 and 4 removing exceedances for the Unnamed tributary to the Chaco
River which is in a tribal area. When comparing between communities with immediate receiving waters
with and without exceedances, under Options 3 and 4, communities with immediate receiving waters
with exceedances had a larger percent of the population identifying as low-income, African-American
(non-Hispanic), Other (non-Hispanic), and Hispanic or Latino than communities with immediate receiving
waters without exceedances (Table 21). Under Options 3 and 4, for these population groups of concern
and Asian (non-Hispanic) populations, small increases in their proportion of the affected population were
observed compared to the baseline (Table 21). This increase is likely the result of the remaining
immediate receiving waters with exceedances having smaller populations with greater proportions of
these population groups of concern.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 22. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk (LECR) Exceedances3 above 1.00 x 10-6 for
Arsenic under Baseline and the Regulatory Options, Organized by Age and Fishing Mode Cohort
National
Average
Baseline
Options 1 and 2
Options 3 and 4
Demographics
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Child, Subsistence Fisher
; Adult, Recreational Fisher b
Percent Low-Income
13.7%
1.1%
5.7%
Not applicable
(NA)
5.7%
NA
5.7%
Percent African
American (non-
Hispanic)
12.2%
0%
7.7%
NA
7.7%
NA
7.7%
Percent American
Indian/Alaska Native
0.7%
0%
1.3%
NA
1.3%
NA
1.3%
Percent Asian
5.4%
1.8%
2.0%
NA
2.0%
NA
2.0%
Percent Native
Hawaiian/Pacific
Islander
0.2%
0%
0.1%
NA
0.1%
NA
0.1%
Percent Other (non-
Hispanic)
2.7%
0.4%
2.4%
NA
2.4%
NA
2.4%
Percent Hispanic/Latino
18.8%
0%
5.7%
NA
5.6%
NA
5.6%
Total Population
1,687
265,971
0
267,658
0
267,658
Count of IRW
1
97
0
98
0
98
Adult, Subsistence Fisher
Percent Low-Income
13.7%
8.2%
5.5%
7.5%
5.7%
1.1%
5.7%
Percent African
American (non-
Hispanic)
12.2%
12.4%
7.3%
0.2%
7.7%
0%
7.7%
Percent American
Indian/Alaska Native
0.7%
9.3%
0.7%
48.4%
0.7%
0%
1.3%
Percent Asian
5.4%
1.7%
2.0%
0.9%
2.0%
1.8%
2.0%
Percent Native
Hawaiian/Pacific
Islander
0.2%
0.2%
0.1%
0%
0.1%
0%
0.1%
Percent Other (non-
Hispanic)
2.7%
3.1%
2.4%
0.4%
2.4%
0.4%
2.4%
Percent Hispanic/Latino
18.8%
4.2%
5.7%
1.3%
5.7%
0%
5.7%
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Section 9—Distributional Analysis of Pollutant Exposures
Table 22. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk (LECR) Exceedances3 above 1.00 x 10-6 for
Arsenic under Baseline and the Regulatory Options, Organized by Age and Fishing Mode Cohort
National
Average
Baseline
Options 1 and 2
Options 3 and 4
Demographics
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Total Population
17,707
249,951
3,334
264,324
1,687
265,971
Count of IRW
9
89
2
96
1
97
Source: 2023 EA
Abbreviations: IRW (immediate receiving water); LECR (lifetime excess cancer risk); NA (not applicable).
a - EPA compared the human health cohort's lifetime average daily dose of the pollutant (i.e., arsenic) from fish ingestion (multiplied by the cancer slope factor) to the LECR of
one-in-a-million to determine exceedances. See the 2023 EAfor more details on the analysis.
b - The same IRW exceeds the LECR of one-in-a-million for the two cohorts listed [i.e., child (subsistence) and adult (recreational) fishers].
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Section 9—Distributional Analysis of Pollutant Exposures
Child Subsistence and Adult Recreational Consumption
Under the baseline, the percent of the population identified as low-income or a racial and ethnic minority
population group is less than the national average in communities with immediate receiving waters with
and without non-cancer HQs greater than one (Table 22). The one exception occurs in communities with
immediate receiving waters without exceedances, where the percent of the population identified as
American Indian or Alaska Native (non-Hispanic) is larger than the national average (Table 22). Comparing
the percent of the population identified as low-income or a racial and ethnic minority population group
between communities with immediate receiving waters with and without exceedances, the results of the
baseline analysis show that communities with immediate receiving waters with exceedances have a
smaller proportions of the population identified as a population groups of concern (Table 22).
The results of the analysis show no arsenic LECR exceedances in any of the affected immediate receiving
waters under each of the four regulatory options (Table 22).
Adult Subsistence Consumption
Under the baseline, in general, the percent of the population identified as low-income or a racial and
ethnic minority population group is less than the national average in communities with immediate
receiving waters with and without arsenic LECR exceedances (Table 22). The one exception occurs in
communities with immediate receiving waters with exceedances, where the percent of the population
identified as African-American (non-Hispanic) and American Indian or Alaska Native (non-Hispanic) are
larger than the national average (Table 22). Comparing the percent of the population identified as low-
income or a racial and ethnic minority population group between communities with immediate receiving
waters with and without exceedances, the results of the baseline analysis show that communities with
immediate receiving waters with exceedances have a larger proportion of the population that is low-
income, African-American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), and Other
(non-Hispanic) (Table 22). Although, when comparing the populations identified as low-income or a racial
ethnic minority population group in absolute terms, the number of people in these groups is higher in
communities with immediate receiving waters without exceedances across all the population groups of
concern (Table 22). This is due to the fact that, under the baseline, the majority of immediate receiving
waters do not have exceedances and the majority of the affected population lives in those areas
(Table 22).
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with arsenic LECR exceedances and the population affected by these exceedances
compared to the baseline (Table 22). Options 3 and 4 generate the largest reductions (Table 22).
Under Options 1 and 2, the percent of the population identified as low-income or a racial and ethnic
minority population group is less than the national average, except for those identified as American
Indian or Alaska Native (non-Hispanic) in communities with immediate receiving waters with exceedances
(Table 22). When comparing between communities with immediate receiving waters with and without
exceedances, the percent of the population is larger in communities with immediate receiving waters
with exceedances for the same population group of concern (Table 22). Under Options 1 and 2, for the
proportion ofthe population identified as American Indian or Alaska Native (non-Hispanic) in
communities with immediate receiving waters with exceedances, a large increase in their proportion of
the affected population was observed relative to the baseline (Table 22). This is likely due to one of the
remaining immediate receiving waters with exceedances under Options 1 and 2 being the Unnamed
tributary to the Chaco River which is located in a tribal area.
Under Options 3 and 4, the percent of the population identified as low-income or a racial and ethnic
minority population groups is less than the national average in communities with immediate receiving
waters with and without exceedances compared to the baseline, except for American Indian and Alaska
Native (non-Hispanic) populations in communities with immediate receiving waters without exceedances
(Table 22). As opposed to Options 1 and 2, this includes the percent ofthe population that identifies as
73
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Section 9—Distributional Analysis of Pollutant Exposures
American Indian and Alaska Native (non-Hispanic) in communities with immediate receiving waters with
exceedances (Table 22). This change is likely due to Options 3 and 4 removing exceedances for the
Unnamed tributary to the Chaco River. When comparing between communities with immediate receiving
waters with and without exceedances, under Options 3 and 4, communities with immediate receiving
waters with exceedances had a smaller percent of the population identifying as a population groups of
concerns across all population groups (Table 22).
9.2.1.1.5 Key Conclusions
Based on the results of the distributional analysis of non-cancer and cancer human health impacts, across
the three analyses, EPA found that under the baseline PEJC were observed largely among affected
American Indian or Alaska Native (non-Hispanic) populations when comparing the percent of the
population affected in communities with immediate receiving waters with non-cancer and cancer
benchmark exceedances to the national average. Making an internal comparison between the affected
population, EPA found PEJC among specific population groups of concern as they comprised a larger
proportion of the population in communities with immediate receiving waters with exceedances than in
communities with immediate receiving waters without non-cancer and cancer exceedances. Analyzing
the regulatory options across the analyses, EPA found that Options 3 and 4 consistently generated the
largest reductions in immediate receiving waters with non-cancer and cancer exceedances and the
population affected by these exceedances. EPA also concluded that Options 3 and 4 consistently
produced the greatest improvements in the distribution of impacts across the population groups of
concern relative to the baseline.
9.2.1.2 Distribution of Health Effects among Subsistence Populations
As the results in Tables 21 and 22 show, under the baseline and regulatory options, the total number of
immediate receiving waters with non-cancer or cancer benchmark exceedances is greater among adult
and child subsistence fish consumers than adult and child recreational fish consumers. Minority
populations, low-income populations, and indigenous people are more likely to consume fish for
subsistence than the general population (2020 EA, Appendix E). Subsistence fish consumers' higher
consumption rates compared to recreational consumers increases their exposure to pollutants and their
risks of adverse health impacts (2020 EA, Appendix E). Therefore, these results indicate the potential for
disproportionately high and adverse health effects under the baseline and regulatory options to
population groups of concern.
9.2.2 Downstream Surface Waters
As part of the economic analysis for the proposed rule, EPA used the D-FATE model to calculate
concentrations of pollutants in downstream reaches of surface waters that receive discharges from steam
electric power plants. EPA used these concentrations to estimate fish tissue concentrations in
downstream reaches of receiving waters under the baseline and regulatory options. For more
information on the D-FATE model and the analysis of downstream pollutant and fish tissue
concentrations, see the 2023 BCA.
EPA then used the modeled fish tissue concentrations as inputs to evaluate human health risks to
populations consuming self-caught fish, because the Agency expects recreational and subsistence fishers
(and their household members) who consume fish caught in the downstream reaches of receiving waters
of steam electric power plant discharges are likely to be affected by changes in pollutant concentrations
in fish tissues. EPA conducted three analyses to evaluate human health effects among relevant cohorts
from various pollutant exposures under the baseline and regulatory options:
• Lead exposure from fish consumption: This analysis evaluated potential neurological and cognitive
impacts to children (ages 0-7) in terms of avoided intelligence quotient (IQ) point losses from
exposure to lead through recreational and subsistence fish consumption.
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Section 9—Distributional Analysis of Pollutant Exposures
• Mercury exposure from fish consumption: This analysis also evaluated potential neurological and
cognitive impacts to children (ages 0-7) in terms of avoided IQ point losses from exposure to mercury
through recreational and subsistence fish consumption.
• Arsenic exposure from fish consumption: This analysis evaluated potential cancer risk impacts to
adults, expressed as avoided cancer cases, from exposure to arsenic through recreational and
subsistence fish consumption.
After completing these analyses, EPA disaggregated health effects within cohorts by racial and ethnic
population group (White, Black, Hispanic, Asian, American Indian and Alaska Native, Other40) and by
income group (above the poverty line or below the poverty line). EPA did this to facilitate an evaluation of
the distribution of health effects within and among these groups to determine where there are
disproportionately high and adverse health impacts to population groups of concern under the baseline
and regulatory options. The results of the analysis are presented and discussed below.41
9.2.2.1 Distribution of Health Impacts Among Children Exposed to Lead through Fish Consumption
Table 23 presents the total IQ points under the baseline and the change in avoided IQ point losses under
each regulatory option, for child subsistence and recreational fish consumers, by race and ethnic
population group.
4a The "Other" category includes populations that identify as Native Hawaiian and Other Pacific Islander, some
other race alone, and two or more races, based on 2019 American Community Survey data (U.S. Census Bureau,
2022a).
41 The results of the downstream analysis are presented as aggregate changes in avoided IQ points losses and
avoided cancer cases for the various racial and ethnic population groups and income groups as a whole, rather
than as changes in avoided IQ point losses and avoided cancer cases for an average individual in a group. EPA
chose to do this because the changes in avoided IQ point losses and avoided cancer cases were small.
Presenting them for an average individual in a group would therefore have resulted in EPA reporting small
fractions of an IQ point or cancer case, which EPA concluded would not be informative. For example, the largest
change under the regulatory options across analyses was 2,480 avoided IQ point losses for children not below
the poverty level exposed to mercury through fish consumption at recreational rates. The change in avoided IQ
point losses, if presented for an average individual in the group, would have been 0.18 avoided IQ point losses
(Table 26). All other results from the downstream analysis with smaller changes would have resulted in even
smaller fractions of an IQ point or cancer case being reported for an average individual.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 23. Modeled Total IQ Points Under the Baseline and Change in Avoided IQ Point Losses under the Regulatory Options Among Child
Subsistence and Recreational Fish Consumers Exposed to Lead through Fish Consumption, by Racial or Ethnic Population Group
Cohort Group
Race/Ethnic Group
Exposed
Population3
Baseline Total IQ
Points'5
Option 1
Option 2
Option 3
Option 4
White
57,963
(68.2%)
897,684 (68.0%)
0
<1.0
<1.0
<1.0
Black
16,124
(19.0%)
251,240 (19.0%)
<1.0
<1.0
<1.0
<1.0
Child Subsistence
Hispanic
4,652
(5.48%)
73,483.1 (5.56%)
0
<1.0
<1.0
<1.0
Asian
3,282
(3.86%)
52,789.5 (4.00%)
0
<1.0
<1.0
<1.0
American Indian and Alaska Native
484
(0.571%)
7,795.60 (0.590%)
0
<1.0
<1.0
<1.0
Other
2,447
(2.88%)
39,390.7 (2.98%)
0
<1.0
<1.0
<1.0
White
844,695
(68.2%)
12,695,700 (68.1%)
0
<1.0
<1.0
<1.0
Black
234,981
(19.0%)
3,546,460 (19.0%)
0
0
<1.0
<1.0
Child Recreation
Hispanic
67,806
(5.48%)
1,025,240 (5.50%)
0
<1.0
<1.0
<1.0
Asian
47,843
(3.86%)
724,459 (3.89%)
0
<1.0
<1.0
<1.0
American Indian and Alaska Native
7,066
(0.571%)
106,996 (0.574%)
0
<1.0
<1.0
<1.0
Other
35,670
(2.88%)
540,744 (2.90%)
0
<1.0
<1.0
<1.0
Notes:
a- The exposed population for each racial/ethnic population group is presented as the number of people exposed and (in parenthesis) the number of people exposed as a share of
the total exposed population for the entire cohort.
b- The baseline total IQ points for each racial and ethnic population group are presented as the total number of IQ points and (in parenthesis) the total number of IQ points as a
share of the total number of IQ points for the entire cohort.
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Section 9—Distributional Analysis of Pollutant Exposures
The results of the distributional analysis of neurological and cognitive health impacts among child
subsistence and recreational fish consumers indicates that under the baseline and regulatory options,
population groups of concern do not experience disproportionately high and adverse impacts compared
to the White population group (Table 23).
For the baseline, a comparison of each racial and ethnic population group's share of the cohort's total IQ
points compared to its share of the cohort's total exposed population showed that Black, Hispanic, Asian,
American Indian and Alaska Native, and other population groups had either the same or a larger share of
IQ points compared to their share of the exposed population (Table 23). In comparison, the White
population group had a smaller share of IQ points compared to its share of the exposed population
(Table 23).
Examining the impact of the regulatory options on avoided IQ point losses in the various racial and ethnic
population groups showed that for both child subsistence and recreational fish consumer cohorts, all of
the regulatory options resulted in avoided IQ point losses, compared to the baseline, across all of the
population groups (Table 23). Additionally, the regulatory options resulted in no change in the share of IQ
points for each population group relative to their share of the exposed population, compared to the
baseline, as the changes in avoided IQ point losses were small (Table 23). For the child subsistence
consumer cohort, Option 1 resulted in avoided IQ points losses for the Black population group, and no
changes in avoided IQ point losses for the other population groups (Table 23). Options 2, 3, and 4
resulted in avoided IQ point losses across all population groups, with Option 4 generating the greatest
combined avoided IQ point losses (Table 23). For the child recreational consumer cohort, Option 1 did not
result in a change in avoided IQ point losses for any of the population groups (Table 23). Option 2
generated avoided IQ point losses across all population groups, except for the Black population group,
which experienced no change in avoided IQ point losses (Table 23). Options 3 and 4 resulted in avoided IQ
point losses across all population groups, with both options resulting in the largest combined avoided IQ
point losses (Table 23).
Table 24 presents the total IQ points under the baseline and change in avoided IQ point losses under each
of the regulatory options for child subsistence and recreational fish consumers, by income group (below
the poverty line or not below the poverty line).
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Section 9—Distributional Analysis of Pollutant Exposures
Table 24. Modeled Total IQ Points under the Baseline and Change in Avoided IQ Point Losses Under the Regulatory Options Among Child
Subsistence and Recreational Fish Consumers Exposed to Lead through Fish Consumption, by Income Group
Cohort Group
Income Group
Exposed
Population3
Baseline Total IQ Points'3
Option 1
Option 2
Option 3
Option 4
Child Subsistence
Below the Poverty Line
12,324 (14.5%)
192,191 (14.5%)
<1.0
<1.0
<1.0
<1.0
Not Below the Poverty Line
72,361 (85.5%)
1,130,190(85.5%)
<1.0
<1.0
<1.0
<1.0
Child Recreation
Below the Poverty Line
179,607(14.5%)
2,708,790 (14.5%)
0
<1.0
<1.0
<1.0
Not Below the Poverty Line
1,058,460
(85.5%)
15,930,800(85.5%)
0
<1.0
2.27
2.27
Notes:
a- The exposed population for each income group is presented as the number of people exposed and (in parenthesis) the number of people exposed as a share of the total
exposed population for the entire cohort.
b- The baseline total IQ points for each income group are presented as the total number of IQ points and (in parenthesis) the total number of IQ points as a share of the total
number of IQ points for the entire cohort.
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Section 9—Distributional Analysis of Pollutant Exposures
The results of the distributional analysis of neurological and cognitive health impacts among both child
subsistence and recreational fish consumers indicate that under the baseline and regulatory options
there are not disproportionately high and adverse impacts to those below the poverty line compared to
those not below the poverty line (Table 24). An additional analysis of IQ points under the baseline and the
change in avoided IQ point losses under each regulatory option for child subsistence and recreational
consumer cohorts by income group, controlling for race and ethnicity, confirmed these conclusions
(Appendix E, Table E-l).
When evaluating results for child subsistence and recreational fish consumer cohorts under the baseline,
a comparison of each income group's share of each cohort's total IQ points compared to its share of each
cohort's total exposed population showed that each income group's share of the total IQ points is
proportionally equivalent to its share of the exposed population (Table 24).
Examining the impact of the regulatory options on avoided IQ point losses in both income groups showed
that for both child subsistence and recreational fish consumers cohorts, all of the regulatory options
resulted in avoided IQ point losses (Table 24). Additionally, while the regulatory options generally resulted
in greater avoided IQ point losses for those not below the poverty line in absolute terms, this did not
change the share of IQ points for each population group relative to their share of the exposed population,
compared to the baseline, as the changes in avoided IQ point losses were small (Table 24). For the child
subsistence consumer cohort, all of the regulatory options resulted in avoided IQ point losses for both
income groups, with Option 4 generating the largest combined avoided IQ point losses (Table 24). For the
child recreational consumer cohort, Option 1 resulted in no change in avoided IQ point losses for both
income groups (Table 24). Options 2, 3, and 4 resulted in avoided IQ point losses for both income groups,
with Options 3 and 4 generating the largest combined avoided IQ point losses (Table 24).
9.2.2.2 Distribution of Health Impacts Among Children Exposed to Mercury Through Fish
Consumption
Table 25 presents the total IQ points under the baseline and the change in avoided IQ point losses under
each regulatory option, for child subsistence and recreational fish consumers, by race and ethnic
population group.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 25. Modeled Total IQ Points Under the Baseline and Change in Avoided IQ Point Losses under the Regulatory Options Among Child
Subsistence and Recreational Fish Consumers Exposed to Mercury through Fish Consumption, by Racial or Ethnic Population Group
Cohort Group
Race/Ethnic Group
Exposed
Populationa
Baseline Total IQ
Pointsb
Option 1
Option 2
Option 3
Option 4
White
7,394 (66.3%)
46,185.9 (59.6%)
364
369
376
376
Black
2,248 (20.2%)
15,496.9 (20.0%)
109
111
114
115
Child Subsistence
Hispanic
666 (5.97%)
5,907.58 (7.62%)
37.0
37.9
40.4
40.4
Asian
457 (4.11%)
5,407.87 (6.98%)
28.5
29.3
31.5
31.6
American Indian and Alaska Native
58 (0.525%)
685.780 (0.885%)
2.93
2.99
3.65
3.65
Other
322 (2.90%)
3,818.80 (4.93%)
27.4
27.8
28.6
28.6
White
107,764
(66.3%)
237,345 (61.7%)
1,870
1,890
1,930
1,930
Black
32,768
(20.2%)
82,806.4 (21.5%)
585
593
611
612
Child Recreation
Hispanic
9,707 (5.97%)
26,146.2 (6.79%)
164
167
179
179
Asian
6,673 (4.11%)
21,015.7 (5.46%)
111
114
122
123
American Indian and Alaska Native
852 (0.525%)
2,665.04 (0.693%)
11.4
11.6
14.2
14.2
Other
4,710 (2.90%)
14,840.4 (3.86%)
106
108
111
111
Notes:
a- The exposed population for each racial/ethnic population group is presented as the number of people exposed and (in parenthesis) the number of people exposed as a share of
the total exposed population for the entire cohort.
b- The baseline total IQ points for each racial/ethnic population group are presented as the total number of IQ points and (in parenthesis) the total number of IQ points as a share
of the total number of IQ points for the entire cohort.
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Section 9—Distributional Analysis of Pollutant Exposures
The results of the distributional analysis of neurological and cognitive health impacts among both child
subsistence and recreational fish consumers indicates that under the baseline and regulatory options
there are not disproportionately high and adverse impacts to population groups of concerns compared to
the White population group (Table 25).
When evaluating results for the child subsistence fish consumer cohort under the baseline, a comparison
of each population group's share of the cohort's total IQ points compared to its share of the cohort's total
exposed population showed that Hispanic, Asian, American Indian and Alaska Native, and Other
population groups' share of IQ points was larger than their share of the exposed population (Table 25).
The Black population group's share of IQ points was smaller than its share of the exposed population,
with 0.2 percent less of a share of the IQ points (Table 25). The White population group had a smaller
share of IQ points compared to its share of the exposed population, with 6.7 percent less of a share of the
IQ points (Table 25). The results for the child recreational fish consumer cohort under the baseline
showed that, for each population group of concern, its share of IQ points was larger than its share of the
exposed population (Table 25). The White population group's share of IQ points was smaller than its
share of the exposed population by 4.6 percent (Table 25).
Examiningthe impact of the regulatory options on avoided IQ point losses in the various racial and ethnic
population groups showed that for both child subsistence and recreational fish consumers cohorts, all of
the regulatory options resulted in avoided IQ point losses, compared to the baseline, across the
population groups (Table 25). Additionally, while the White population group received the greatest
avoided IQ point losses under each of the regulatory options, this resulted in no change in the share of IQ
points for each population group relative to their share of the exposed population, compared to the
baseline(Table 25). Of the regulatory options, Option 4 resulted in the largest combined avoided IQ point
losses compared to the baseline (Table 25).
Table 26 presents the total IQ points under the baseline and change in avoided IQ point losses under each
of the regulatory options for child subsistence and recreational fish consumers, by income group (below
the poverty line or not below the poverty line).
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Section 9—Distributional Analysis of Pollutant Exposures
Table 26. Modeled Total IQ Points Under the Baseline and Change in Avoided IQ Point Losses under the Regulatory Options Among Child
Subsistence and Recreational Fish Consumers Exposed to Mercury through Fish Consumption, by Income Group
Cohort Group
Income Group
Exposed
Population3
Baseline Total IQ Points'3
Option 1
Option 2
Option 3
Option 4
Child Subsistence
Below the Poverty Line
1,675 (15.0%)
11,796.6 (15.2%)
95.4
96.6
99.2
99.2
Not Below the Poverty Line
9,473 (85.0%)
65,706.2 (84.8%)
474
481
496
496
Child Recreation
Below the Poverty Line
24,419 (15.0%)
58,722.6 (15.3%)
478
484
496
496
Not Below the Poverty Line
138,058 (85.0%)
326,096 (84.7%)
2,370
2,400
2,480
2,480
Notes:
a- The exposed population for each income group is presented as the number of people exposed and (in parenthesis) the number of people exposed as a share of the total
exposed population for the entire cohort.
b- The baseline total IQ points for each income group are presented as the total number of IQ points and (in parenthesis) the total number of IQ points as a share of the total
number of IQ points for the entire cohort.
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Section 9—Distributional Analysis of Pollutant Exposures
The results of the distributional analysis of neurological and cognitive health impacts among both child
subsistence and recreational fish consumers indicate that under the baseline and regulatory options
there are not disproportionately high and adverse impacts to those below the poverty line compared to
those not below the poverty line (Table 26). An additional analysis of IQ points under the baseline and the
change in avoided IQ point losses under each regulatory option for child subsistence and recreational
consumer cohorts by income group, controlling for race and ethnicity, confirmed these conclusions
(Appendix E, Table E-2).
The results for the child subsistence and recreational fish consumer cohorts under the baseline showed
that those below the poverty line had a larger share of IQ points compared to their share of the exposed
population, while those not below the poverty line had a smaller share of IQ points compared to their
share of the exposed population by 0.2 and 0.3 percent, respectively (Table 26).
Examining the impact of the regulatory options on avoided IQ point losses by income group showed that
for both child subsistence and recreational fish consumers cohorts, all of the regulatory options resulted
in avoided IQ point losses for both those below the poverty line and those not below the poverty line,
compared to the baseline (Table 26). Additionally, while under each of the regulatory options those not
below the poverty line had the greatest avoided IQ point losses in absolute terms, the regulatory options
resulted in no change in the share of IQ points for each income group relative to their share of the
exposed population, compared to the baseline (Table 26). Of the regulatory options, Options 3 and 4
resulted in the largest combined avoided IQ point losses, compared to the baseline (Table 26).
9.2.2.3 Distribution of Health Effects Among Adults Exposed to Arsenic Through Fish Consumption
Table 27 presents the total cancer cases under the baseline and change in avoided cancer cases under
each of the regulatory options for adult subsistence and recreational fish consumers, by race and ethnic
population group.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 27. Modeled Total Cancer Cases Under the Baseline and Change in Avoided Cancer Cases under the Regulatory Options Among Adult
Subsistence and Recreational Fish Consumers Exposed to Arsenic through Fish Consumption, by Racial or Ethnic Population Group
Cohort Group
Race/Ethnic Group
Exposed
Population3
Baseline Total
Cancer Cases'5
Option 1
Option 2
Option 3
Option 4
White
714,579 (71.2%)
40.7 (65.4%)
<1.0
<1.0
<1.0
<1.0
Black
171,082(17.0%)
10.4 (16.7%)
<1.0
<1.0
<1.0
<1.0
Hispanic
47,940 (4.80%)
3.74 (6.01%)
<1.0
<1.0
<1.0
<1.0
Adult Subsistence
Asian
37,985 (3.80%)
4.01 (6.45%)
<1.0
<1.0
<1.0
<1.0
American Indian and Alaska
Native
5,352 (0.500%)
0.555 (0.892%)
<1.0
<1.0
<1.0
<1.0
Other
26,838 (2.70%)
2.82 (4.53%)
<1.0
<1.0
<1.0
<1.0
White
10,413,558
(71.2%)
209 (67.4%)
<1.0
<1.0
<1.0
<1.0
Black
2,493,173
(17.0%)
55.7 (18.0%)
<1.0
<1.0
<1.0
<1.0
Adult Recreation
Hispanic
698,634(4.80%)
16.5 (5.34%)
<1.0
<1.0
<1.0
<1.0
Asian
553,568 (3.80%)
15.6 (5.03%)
<1.0
<1.0
<1.0
<1.0
American Indian and Alaska
Native
78,007 (0.500%)
2.15 (0.695%)
<1.0
<1.0
<1.0
<1.0
Other
391,112(2.70%)
11.0 (3.54%)
<1.0
<1.0
<1.0
<1.0
Notes:
a- The exposed population for each racial and ethnic population group is presented as the number of people exposed and (in parentheses) the number of people exposed as a
share of the total exposed population for the entire cohort.
b- The baseline total cancer cases for each racial and ethnic population group are presented as the total number of cases for the group and (in parentheses) the total number of
cases for the group as a share of the total number of cases for the entire cohort.
84
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Section 9—Distributional Analysis of Pollutant Exposures
The results of the distributional analysis of cancer cases among both adult subsistence and recreational
fish consumers indicates that under the baseline and regulatory options there are disproportionately high
and adverse impacts to population groups of concern compared to the White population group (Table
27).
When evaluating results for the adult subsistence fish consumer cohort under the baseline, a comparison
of each racial and ethnic population group's share of the cohort's total cancer cases compared to its
share of the cohort's total exposed population showed that Hispanic, Asian, American Indian and Alaska
Native, and Other population groups' share of total cancer cases was larger than its share of the exposed
population (Table 27). The Black population group's share of total cancer cases was smaller than its share
of the exposed population by 0.3 percent (Table 27). The White population group had a smaller share of
total cancer cases compared to its share of the exposed population by 5.8 percent (Table 27). The results
for the child recreational fish consumer cohort under the baseline showed that, for each population
group of concern, its share of total cancer cases was larger than its share of the exposed population
(Table 27). The White population group's share of total cancer cases was smaller than its share of the
exposed population by 3.8 percent (Table 27).
Examining the impact of the regulatory options on avoided cancer cases in the various racial and ethnic
groups showed that for both child subsistence and recreational fish consumers cohorts, all of the
regulatory options resulted in avoided cancer cases across all population groups compared to the
baseline (Table 27). Of the regulatory options, Option 4 resulted in the greatest combined avoided cancer
cases compared to the baseline (Table 27). While the regulatory options resulted in avoided cancer cases
across population groups, the absolute changes in cancer cases under each of the regulatory options did
not result in a change in the distribution of the share of total cancer cases relative to the share of the
total population among the population groups compared to the baseline as the changes in cancer cases
were small (Table 27). Under each of the regulatory options, disproportionately high and adverse impacts
were still observed among population groups of concern compared to the White population group
(Table 27).
Table 28 presents the total cancer cases under the baseline and change in avoided cancer cases under
each of the regulatory options for child subsistence and recreational fish consumers, by income group
(below the poverty line or not below the poverty line).
85
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Section 9—Distributional Analysis of Pollutant Exposures
Table 28. Modeled Total Cancer Cases Under the Baseline and Change in Avoided Cancer Cases under the Regulatory Options Among Adult
Subsistence and Recreational Fish Consumers Exposed to Arsenic through Fish Consumption, by Income Group
Cohort Group
Income Group
Exposed
Population3
Baseline Total Cancer Cases'3
Option 1
Option 2
Option 3
Option 4
Adult Subsistence
Below the Poverty Line
135,371
(13.5%)
8.23 (13.2%)
<0.1
<0.1
<1.0
<1.0
Not Below the Poverty Line
868,405
(86.5%)
54.0 (86.8%%)
<1.0
<1.0
<1.0
<1.0
Adult Recreation
Below the Poverty Line
1,972,774
(13.5%)
46.1 (13.3%)
<1.0
<1.0
<1.0
<1.0
Not Below the Poverty Line
12,655,279
(86.5%)
269 (86.7%)
<1.0
<1.0
<1.0
<1.0
Notes:
a- The exposed population for each income group is presented as the number of people exposed and (in parentheses) the number of people exposed as a share of the total
exposed population for the entire cohort.
b- The baseline total cancer cases for each income group are presented as the total number of cancer cases and (in parentheses) the total number of cancer cases as a share of the
total number of cancer cases for the entire cohort.
86
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Section 9—Distributional Analysis of Pollutant Exposures
The results of the distributional analysis of cancer cases among both adult subsistence and recreational
fish consumers indicate that under the baseline and regulatory options there are not disproportionately
high and adverse impacts to those below the poverty line compared to those not below the poverty line
(Table 28). An additional analysis of cancer cases under the baseline and the change in avoided cancer
cases under each regulatory option for adult subsistence and recreational consumer cohorts by income
group, controlling for race and ethnicity, confirmed these conclusions (Appendix E, Table E-3).
The results for adult subsistence and recreational fish consumer cohorts under the baseline showed that
that those below the poverty line had a smaller share of cancer cases compared to their share of the
exposed population, while those not below the poverty line had a larger share of cancer cases compared
to their share of the exposed population (Table 28).
Examining the impact of the regulatory options on avoided cancer cases in both income groups showed
that for both adult subsistence and recreational fish consumers cohorts, all of the regulatory options
resulted in avoided cancer cases compared to the baseline (Table 28). While those not below the poverty
line received the greatest avoided cancer cases under each of the regulatory options in absolute terms,
this did not result in a change in the distribution of the share of total cancer cases relative to the share of
the exposed population, compared to the baseline, among the income groups as the changes in avoided
cancer cases were relatively small (Table 28). Of the regulatory options, Option 4 resulted in the most
combined avoided cancer cases compared to the baseline (Table 28).
9.2.2.4 Key Conclusions
The results of EPA's analysis of human health impacts resulting from exposures among fish consumers to
lead, mercury, and arsenic in downstream surface waters did not show PEJC in the baseline or under the
regulatory options when evaluating neurological and cognitive impacts from lead and mercury exposure
among child subsistence and recreational fish consumers, both when evaluating the distribution of
impacts by race and ethnic group and by income group. However, disproportionately high and adverse
impacts were identified in the baseline and under the regulatory options when evaluating cancer risk
impacts from arsenic exposure among adult subsistence fishers when evaluating the distribution of
impacts by race and ethnic group. Such distributional impacts were not identified when evaluating the
distribution of cancer risk impacts by income group. For all human health endpoints, across population
groups of concern and fish consumers, EPA found that all of the regulatory options increased avoided IQ
point losses and avoided cancer cases, with Option 4 producing the greatest improvements. Although,
given the relatively small magnitude of these changes under the regulatory options, EPA concluded that
the regulatory options do not cause PEJC relative to the baseline and, in the case of can risk impacts
among adult subsistence fish consumers, do not mitigate or exacerbate PEJC under the baseline among
racial and ethnic groups.
9.3 Drinking Water
Along with the pollutants evaluated in the surface water analysis, EPA also analyzed changes in bromide
loadings from steam electric power plant discharges of FGD wastewater and BA transport water. The
presence of bromide in surface water is not considered to pose a risk to human health as the bromide ion
has a low degree of toxicity, but as surface waters transport bromide discharges downstream to drinking
water treatment facility intakes, bromide can be drawn into the treatment systems and undergo chemical
87
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Section 9—Distributional Analysis of Pollutant Exposures
changes that can potentially pose risks to human health through drinking water42, 43. Of particular
concern to EPA was bromide's contribution to the formation of brominated disinfection byproducts
(DBPs) during disinfection processes that occur as part of standard drinking water treatment. When
surface water containing bromide is disinfected using chlorine a chemical change occurs which produces
hypobromite (BrCT) which reacts with organic matter in the water to produce brominated and mixed
chloro-bromo DBPs, including trihalomethanes (referred to as TTHM). There is evidence that exposure to
TTHM through drinking water is linked to the incidence of bladder cancer. For more information on
bromide loadings from steam electric power plants, the formation of brominated and mixed chloro-
bromo DBPs, and associated human health impacts see Section 4 of the 2023 BCA.
Based on this understanding of potential human health risks related to exposure to TTHM through
drinking water, EPA evaluated the distribution of TTHM under the regulatory options in communities
served by drinking water system identified as intaking water directly or indirectly (i.e., purchasing water)
from surface waters receiving bromide discharges from steam electric power plants. Additionally, EPA
analyzed the distribution of health impacts, specifically incidence of bladder cancer, under the regulatory
options in these communities. These analyses were performed to determine whether PEJC related to
exposures to TTHM and bladder cancer incidence exist under the regulatory options. The following
sections present and discuss the results of these analyses.
9.3.1 Distribution of TTHM Exposures Among Affected Communities
To evaluate the distribution of TTHM exposures among communities served by drinking water systems,
EPA first estimated bromide concentrations in downstream surface waters identified as receiving FGD
wastewater and BA transport water discharges from steam electric power plants under the baseline and
regulatory options using the D-FATE model. EPA then used information from the SDWIS dataset to
determine what PWS downstream of the steam electric power plants would be impacted based on
whether they directly or indirectly intake source water from an identified downstream surface water
receiving bromide discharges from a plant. Combining PWS information from SDWIS with reach-level
bromide concentrations modeled in D-FATE, EPA calculated system-level changes in bromide
concentrations in the source waters under each of the regulatory options. Using research estimating
changes in TTHM levels as a function of changes in bromide levels, EPA used the system-level changes in
bromide concentrations under each of the regulatory options to predict TTHM concentration changes.
Finally, EPA estimated exposures to changes in TTHM concentrations using information on zip codes
4Z Halogens discharged by steam electric plants include both bromide and iodine, but EPA quantified only effects
associated with brominated DBPs. In vitro toxicology studies with bacteria and mammalian cells have
documented evidence of genotoxic (including mutagenic), cytotoxic, tumorigenic, and developmental toxicity
properties of iodinated DBPs, but the available data are insufficient at this time to determine the extent of
iodinated DBP's contribution to adverse human health effects from exposure to treated drinking water.
43, EPA acknowledges that other pollutants discharged by steam electric power plants to surface waters [e.g., lead,
mercury, and arsenic) may affect the quality of water used for public drinking water systems. The pollutants
may not be removed adequately during treatment at a drinking water treatment plant and people may then be
exposed to such harmful pollutants through ingestion, as well as inhalation and dermal absorption [e.g.,
showering, bathing). Public drinking water supplies are subject to legally enforceable MCLs, which specify the
highest level of a pollutant that is allowed in drinking water, established by EPA. The MCL is based on the MCL
Goal (MCLG), which is the level of a contaminant in drinking water below which there is no known or expected
risk to human health. EPA sets the MCL as close to the MCLG as possible, with consideration for the best
available treatment technologies and costs. For the purpose of analyzing the human health benefits of the
regulatory options, EPA assumes that treated water meets applicable MCLs in the baseline. To assess potential
for changes in health risk from exposure to arsenic, lead, and thallium in drinking water, EPA estimated changes
in pollutant levels in source waters downstream from steam electric power plants under each regulatory
option. The results of this analysis are presented in Section 4.3.2.3 of the 2023 BCA. Additionally, a
distributional analysis using these results is presented in Section 9.2.
88
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Section 9—Distributional Analysis of Pollutant Exposures
served by each system from UCMR4 and SDWIS to estimate the population served and exposed to TTHM
through drinking water. For a more detailed discussion of EPA methodology for estimating TTHM
exposures, see Section 4 of the 2023 BCA.
The results of the analysis are presented in Table 29. Given the number of systems that EPA identified as
being potentially impacted by bromide discharges, changes in TTHM concentrations are presented at the
state level for ease of comprehension. Therefore, changes in TTHM concentrations presented in Table 29
were calculated by weighting the modeled changes in TTHM concentrations under each of the regulatory
options across all affected drinking water systems in each state based on the population served.
Information on changes in TTHM concentrations under each of the regulatory options is combined with
information on socioeconomic characteristics of the exposed populations collected from the U.S. Census
Bureau's 2015 to 2019 ACS dataset to facilitate assessment of distributional impacts.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 29. Modeled Changes in TTHM Concentrations Under the Regulatory Options Among Potentially
Affected Drinking Water Systems, by State
# Potentially
Percent
Percent
Percent
Percent
Native
Percent
Option 1
Option 2
Option 3
Option 4
State
Affected
PWS
Served
Low-
Income3
African -
American3
Indian/Alask
a Native a
Asian3
Hawaiian/
Pacific
Islander3
Othera
Hispanic/
Latino3
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
AL
81
2,008,103
16.6%
23.2%
0.5%
1.4%
0.1%
2.3%
5.7%
0
0
-5.6
27
-5.7
27
-18
29
AZ
9
14,815
15.9%
2.9%
34.6%
0.8%
0.2%
1.9%
22.1%
0
0
0
10
<-1.0
10
<-1.0
10
CA
96
12,191,421
13.4%
6.4%
0.2%
14.9%
0.3%
2.8%
43.3%
0
0
0
96
<-1.0
96
<-1.0
96
DC
2
632,323
14.3%
39.5%
0.2%
5.4%
0.1%
3.0%
9.9%
0
0
0
0
<-1.0
2
<-1.0
2
GA
14
643,252
20.1%
39.3%
0.3%
1.3%
0.0%
2.3%
8.8%
0
0
-1.9
2
-2.0
2
-2.0
2
IA
3
159,823
13.4%
7.5%
0.2%
2.8%
0.0%
2.9%
6.5%
0
0
<-1.0
2
<-1.0
3
<-1.0
3
IL
31
549,576
14.5%
16.8%
0.2%
1.6%
0.0%
2.4%
6.1%
0
0
0
0
-11
24
-11
31
IN
5
200,792
34.3%
33.5%
0.4%
0.1%
1.0%
4.4%
4.9%
0
0
-8.3
5
-8.3
5
-8.4
5
KS
12
168,609
10.9%
7.2%
0.7%
1.3%
0.0%
3.1%
10.5%
0
0
-23
12
-23
12
-23
12
KY
38
349,733
18.4%
5.4%
0.1%
0.6%
0.0%
1.9%
4.5%
0
0
-11
14
-11
14
-11
27
LA
18
968,256
18.7%
40.0%
0.3%
3.2%
0.0%
2.0%
9.9%
0
0
-12.3
18
-12.3
18
-12.4
18
MA
10
358,066
13.3%
3.8%
0.2%
9.5%
0.0%
1.9%
29.0%
-5.3
10
-5.3
10
-5.4
10
-5.4
10
MD
19
3,936,765
10.9%
39.0%
0.2%
8.0%
0.1%
3.2%
12.0%
0
0
0
0
<-1.0
11
<-1.0
11
MN
9
667,615
15.4%
15.8%
0.8%
5.4%
0.0%
3.9%
8.3%
0
0
0
0
<-1.0
9
<-1.0
9
MO
19
1,824,039
10.7%
23.0%
0.1%
3.7%
0.0%
2.5%
3.0%
0
0
-24
19
-24
19
-24
19
NC
37
1,337,529
13.6%
57.9%
0.1%
2.0%
0.0%
2.5%
7.5%
0
0
0
0
<-1.0
36
-17
36
ND
11
33,052
7.6%
1.3%
3.3%
0.7%
0.0%
2.1%
3.2%
0
0
-7.7
12
-7.7
12
-7.7
12
NE
9
13,097
8.1%
0.8%
0.1%
0.2%
0.1%
1.2%
2.7%
0
0
-4.6
9
-4.6
9
-4.6
9
NH
1
87,932
10.8%
3.0%
0.1%
7.6%
0.0%
2.9%
15.1%
<-1.0
1
<-1.0
1
<-1.0
1
<-1.0
1
NV
8
2,174,286
14.4%
11.2%
0.4%
9.0%
0.6%
4.0%
32.5%
0
0
0
0
<-1.0
7
<-1.0
8
OH
19
109,283
23.4%
6.1%
0.3%
1.0%
0.0%
2.9%
2.4%
0
0
-5.0
19
-5.1
19
-5.8
19
OK
20
33,187
22.2%
1.1%
31.0%
0.8%
0.2%
9.6%
6.3%
0
0
0
0
<-1.0
20
<-1.0
20
PA
68
3,598,707
12.0%
11.9%
0.1%
3.9%
0.0%
2.5%
5.7%
0
0
-7.4
40
-7.6
40
-7.6
40
90
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Section 9—Distributional Analysis of Pollutant Exposures
Table 29. Modeled Changes in TTHM Concentrations Under the Regulatory Options Among Potentially
Affected Drinking Water Systems, by State
# Potentially
Percent
Percent
Percent
Percent
Native
Percent
Option 1
Option 2
Option 3
Option 4
State
Affected
PWS
Served
Low-
Income3
African -
American3
Indian/Alask
a Native a
Asian3
Hawaiian/
Pacific
Islander3
Othera
Hispanic/
Latino3
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
SC
43
473,094
13.0%
22.6%
0.5%
1.5%
0.1%
2.6%
4.8%
0
0
0
0
<-1.0
18
-4.1
18
SD
98
135,807
14.9%
1.0%
11.1%
1.9%
0.1%
2.1%
3.6%
0
0
-82
106
-82
106
-82
106
TN
43
2,113,168
12.4%
16.6%
0.2%
2.7%
0.1%
2.6%
7.5%
0
0
0
0
0
0
<-1.0
28
VA
35
3,090,649
7.5%
15.7%
0.2%
12.4%
0.1%
4.2%
14.5%
0
0
0
0
<-1.0
34
-7.0
35
WV
21
256,821
19.6%
3.9%
0.1%
2.1%
0.0%
2.9%
2.3%
0
0
-3.5
8
-3.8
21
-4.2
21
Total
779
38,129,800
-6.3
11
-203.6
410
-225.5
585
-265.2
637
US
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Notes:
a) Socioeconomic characteristics are population-weighted to reflect differences in populations served by potentially affected PWS within each state, as well as characteristics of different ZCTAs
intersected by the PWS service areas. Each racial and ethnic category besides Hispanic or Latino represent the subset of the race and ethnicity that is identified as "non-Hispanic".
b) This column shows the average change in TTHM concentrations (in ug/L) under each of the regulatory options. The change in TTHM concentration was weighted by the populations of the
potentially affected PWS in each state.
c) Delaware and Mississippi each had one downstream PWS, but neither was estimated to be impacted by any regulatory option for TTHM concentrations.
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Section 9—Distributional Analysis of Pollutant Exposures
The results of EPA's analysis showed that, across all states and affected systems, all of the regulatory
options resulted in a decrease in the concentration of TTHM in drinking water (Table 29).
Under Option 1, reductions in TTHM concentrations are observed across 11 systems in two states -
Massachusetts and New Hampshire (Table 29). Populations served by potentially affected systems in
Massachusetts have larger proportions of Asian (non-Hispanic) and Hispanic or Latino people than the
national average (Table 29). Additionally, populations served by potentially affected systems in New
Hampshire have larger proportions of Asian (non-Hispanic) and Other (non-Hispanic) people than the
national average (Table 29).
Option 2 results in reductions in TTHM concentrations across 410 systems in 16 states (Table 29). Of
these 16 states, 14 have populations served by affected systems where the percent of the population for
at least one population group of concern is above the national average (Table 29). For five states which
have one population group of concern above the national average, the median change in TTHM
concentrations observed under Option 2 is about -ll|ag/L (Table 29). Across eight states which have two
population groups of concern above the national average, the median change in TTHM concentrations
observed under Option 2 is about -4.4|ag/L (Table 29). Lastly, for one state which has three or more
population groups of concern above the national average, the change in TTHM concentrations observed
under Option 2 is about -8.3|ag/L (Table 29).
Under Option 3, reductions in TTHM concentrations are observed across 585 systems in 27 states (Table
29). Of these 27 states, 25 have populations served by affected systems where the percent of the
population for at least one population group of concern is above the national average (Table 29). For
seven states which have one population group of concern above the national average, the median change
in TTHM concentrations observed under Option 3 is about -7.7|ag/L (Table 29). Across nine states which
have two population groups of concern above the national average, the median change in TTHM
concentrations observed under Option 3 is about -5.4|ag/L (Table 29). Lastly, for nine states which have
three or more population groups of concern above the national average, the change in TTHM
concentrations observed under Option 3 is about -l|ag/L (Table 29).
Option 4 results in reductions in TTHM concentrations in 637 systems across all 28 states with potentially
affected systems. Of these states, 26 have populations served by affected systems where the percent of
the populations for at least one population group of concern is above the national average (Table 29). For
eight states which have one population group of concern above the national average, the median change
in TTHM concentrations observed under Option 4 is about -9.3|ag/L (Table 29). Across nine states which
have two population groups of concern above the national average, the median change in TTHM
concentrations observed under Option 4 is about -5.4|ag/L (Table 29). Finally, for nine states which have
three or more population groups of concern above the national average, the median change in TTHM
concentrations observed under Option 4 is about -l|ag/L (Table 29).
9.3.2 Distribution of Bladder Cancer Cases Among Affected Communities
To model the relationship between estimated changes in lifetime TTHM exposures and bladder cancer
cases, EPA used a life table approach which estimates age-specific changes in bladder cancer probability
and models subsequent bladder cancer mortality. The life table approach enables quantification of
complex regulatory scenarios that involve variable pollutant changes over time. For this analysis, EPA
assumed that the population affected by estimated changes in bromide discharges from steam electric
power plants is exposed to baseline TTHM concentrations before implementation of the proposed rule-
before 2025-and to alternative TTHM concentrations from 2025-2049 to be consistent with the
framework for evaluating costs and benefits. Therefore, EPA modeled changes in bladder cancer health
outcomes resulting from changes in TTHM exposures from 2025-2049. Recognizing that changes in
cancer incidence can occur long after exposure, associated changes in bladder cancer incidence were
modeled through 2125, though for only the changes attributable to changes in TTHM exposure estimated
in the 2025-2049 timeframe. Using available data on bladder cancer incidence and mortality and modeled
relationships between changes in TTHM concentrations and changes in lifetime bladder cancer risk, EPA
92
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Section 9—Distributional Analysis of Pollutant Exposures
calculated changes in bladder cancer incidence and mortality under the regulatory options. For a more
detailed discussion of EPA's methodology for estimating bladder cancer incidence and mortality, see
Section 4 of the 2023 BCA.
The results of the analysis are presented in Table 30 and Table 31. Given the number of systems that EPA
identified as being potentially impacted by changes in bromide discharges, changes in bladder cancer
incidence and mortality are presented at the state level for ease of comprehension. Similar to the analysis
of changes in TTHM concentration, information on changes in bladder cancer incidence and mortality
under each of the regulatory options is combined with information on socioeconomic characteristics of
the exposed populations collected from the U.S. Census Bureau's 2015 to 2019 ACS dataset to facilitate
assessment of distributional impacts.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 30. Modeled Changes in Total Bladder Cancer Cases Avoided Under the Regulatory Options Among
Potentially Affected Drinking Water Systems, by State
a
Percent
Percent
Option 1
Option 2
Option 3
Option 4
State
Potentially Population
Affected Served
PWS
Percent
Low-
Income3
Percent
African-
American3
American
Indian/
Alaska
Native3
Percent
Asian3
Native
Hawaiian/
Pacific
Islander3
Percent
Other3
Percent
Hispanic/
Latino3
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
AL
81
2,008,103
16.6%
23.2%
0.5%
1.4%
0.1%
2.3%
5.7%
0
0
1.5
9
1.6
9
15
12
CA
96
12,191,421
13.4%
6.4%
0.2%
14.9%
0.3%
2.8%
43.3%
0
0
0
0
<1.0
1
<1.0
1
DC
2
632,323
14.3%
39.5%
0.2%
5.4%
0.1%
3.0%
9.9%
0
0
0
0
<1.0
1
<1.0
1
GA
14
643,252
20.1%
39.3%
0.3%
1.3%
0.0%
2.3%
8.8%
0
0
1.8
2
1.9
2
1.9
2
IL
31
549,576
14.5%
16.8%
0.2%
1.6%
0.0%
2.4%
6.1%
0
0
5.3
11
5.3
11
5.3
11
IN
5
200,792
34.3%
33.5%
0.4%
0.1%
1.0%
4.4%
4.9%
0
0
7.3
5
7.4
5
7.4
5
KS
12
168,609
10.9%
7.2%
0.7%
1.3%
0.0%
3.1%
10.5%
0
0
9.7
7
9.7
7
9.7
7
KY
38
349,733
18.4%
5.4%
0.1%
0.6%
0.0%
1.9%
4.5%
0
0
3
10
3
10
3.2
11
LA
18
968,256
18.7%
40.0%
0.3%
3.2%
0.0%
2.0%
9.9%
0
0
14
15
14
15
14
15
MA
10
358,066
13.3%
3.8%
0.2%
9.5%
0.0%
1.9%
29.0%
4.0
8
4.0
8
4.1
8
4.1
8
MD
19
3,936,765
10.9%
39.0%
0.2%
8.0%
0.1%
3.2%
12.0%
0
0
0
0
<1.0
1
<1.0
1
MO
19
1,824,039
10.7%
23.0%
0.1%
3.7%
0.0%
2.5%
3.0%
0
0
44
15
44
15
44
15
NC
37
1,337,529
13.6%
57.9%
0.1%
2.0%
0.0%
2.5%
7.5%
0
0
0
0
<1.0
1
17
12
ND
11
33,052
7.6%
1.3%
3.3%
0.7%
0.0%
2.1%
3.2%
0
0
<1.0
4
<1.0
4
<1.0
4
NE
9
13,097
8.1%
0.8%
0.1%
0.2%
0.1%
1.2%
2.7%
0
0
0.1
1
0.1
1
0.1
1
NH
1
87,932
10.8%
3.0%
0.1%
7.6%
0.0%
2.9%
15.1%
1.3
1
1.3
1
1.3
1
1.3
1
OH
19
109,283
23.4%
6.1%
0.3%
1.0%
0.0%
2.9%
2.4%
0
0
<1.0
2
<1.0
2
<1.0
2
PA
68
3,598,707
12.0%
11.9%
0.1%
3.9%
0.0%
2.5%
5.7%
0
0
11
14
12
14
12
14
SC
43
473,094
13.0%
22.6%
0.5%
1.5%
0.1%
2.6%
4.8%
0
0
0
0
0
0
1.6
8
SD
98
135,807
14.9%
1.0%
11.1%
1.9%
0.1%
2.1%
3.6%
0
0
1.6
12
1.6
12
1.6
12
VA
35
3,090,649
7.5%
15.7%
0.2%
12.4%
0.1%
4.2%
14.5%
0
0
0
0
0.3
3
4.0
9
WV
21
256,821
19.6%
3.9%
0.1%
2.1%
0.0%
2.9%
2.3%
0
0
1.6
3
1.6
3
1.9
3
Total
687
32,966,906
5.3
9
108.2
119
113.9
126
149.1
155
94
-------
Section 9—Distributional Analysis of Pollutant Exposures
Table 30. Modeled Changes in Total Bladder Cancer Cases Avoided Under the Regulatory Options Among
Potentially Affected Drinking Water Systems, by State
ft
Percent
Percent
Option 1
Option 2
Option 3
Option 4
State
Potentially
Affected
PWS
Population
Served
Percent
Low-
Income3
Percent
African-
American3
American
Indian/
Alaska
Native3
Percent
Asian3
Native
Hawaiian/
Pacific
Islander3
Percent
Other3
Percent
Hispanic/
Latino3
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
US
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Notes:
a) Socioeconomic characteristics are population-weighted to reflect differences in populations served by potentially affected PWS within each state, as well as characteristics of different ZCTAs
intersected by the PWS service areas. Each racial and ethnic category besides Hispanic or Latino represent the subset of the race and ethnicity that is identified as "non-Hispanic".
b) This column shows the total number of bladder cancer cases avoided under each of the regulatory options over the period of analysis.
c) Arizona, Delaware, Iowa, Minnesota, Mississippi, Nevada, Oklahoma, and Tennessee had 94 PWSs with very small changes in TTHM concentrations that resulted in no estimated changes in bladder
cancer cases under any regulatory option.
95
-------
Section 9—Distributional Analysis of Pollutant Exposures
The results of EPA's analysis showed that across all states and affected, all of the regulatory options result
in increases in the number of bladder cancer cases avoided over the period of analysis (Table 30).
Under Option 1, increases in the number of bladder cancer cases avoided are observed across nine
systems in two states-Massachusetts and New Hampshire (Table 30). Populations served by potentially
affected systems in Massachusetts have larger proportions of Asian (non-Hispanic) and Hispanic or Latino
people than the national average (Table 30). Additionally, populations served by potentially affected
systems in New Hampshire have larger proportions of Asian (non-Hispanic) and Other (non-Hispanic)
people than the national average (Table 30).
Option 2 results in increases in bladder cancer cases avoided across 119 systems in 16 states (Table 30).
Of these 16 states, 14 have populations served by affected systems where the percent of the population
for at least one population group of concern is above the national average (Table 30). For four states
which have one population group of concern above the national average, the median change in bladder
cancer cases avoided observed under Option 2 is about 6.35 cases (Table 30). Across nine states which
have two population groups of concern above the national average, the median change in bladder cancer
cases avoided observed under Option 2 is about 1.6 cases (Table 30). Lastly, for one state which has three
or more population groups of concern above the national average, the change in bladder cancer cases
avoided observed under Option 2 is about 7.3 cases (Table 30).
Under Option 3, increases in bladder cancer cases avoided are observed across 126 systems in 21 states
(Table 30). Of these 21 states, 19 have populations served by affected systems where the percent of the
population for at least one population group of concern is above the national average (Table 30). For five
states which have one population group of concern above the national average, the median change in
bladder cancer cases avoided observed under Option 3 is about three cases (Table 30). Across nine states
which have two population groups of concern above the national average, the median change in bladder
cancer cases avoided observed under Option 3 is about 1.6 cases (Table 30). Lastly, for five states which
have three or more population groups of concern above the national average, the median change in
bladder cancer cases avoided observed under Option 3 is about one case (Table 30).
Option 4 results in increases in the number of bladder cancer cases avoided across 155 systems in all 22
states with potentially affected systems (Table 30). Of these states, 20 have populations served by
affected systems where the percent of the populations for at least one population group of concern is
above the national average (Table 30). For six states which have one population group of concern above
the national average, the median change in bladder cancer cases avoided observed under Option 4 is
about 6.45 cases (Table 30). Across eight states which have two population groups of concern above the
national average, the median change in bladder cancer cases avoided observed under Option 4 is about
1.9 cases (Table 30). Finally, for five states which have three or more population groups of concern above
the national average, the median change in bladder cancer cases avoided observed under Option 4 is
about one case (Table 30).
96
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Section 9—Distributional Analysis of Pollutant Exposures
Table 31. Modeled Changes in Total Excess Bladder Cancer Deaths Avoided Under the Regulatory Options
Among Potentially Affected Drinking Water Systems, by State
Option 1
Option 2
Option 3
Option 4
Percent
Percent
State
# Potentially
Affected
PWS
Population
Served
Percent
Low-
Income3
Percent
African-
American3
American
Indian/
Alaska
Percent
Asian3
Native
Hawaiian/
Pacific
Percent
Other3
Percent
Hispanic/
Latino3
Deaths
Avoided
PWS
(#)
Deaths
Avoided
PWS
(#)
Deaths
Avoided
PWS
(#)
Deaths
Avoided
PWS
(#)
Native3
Islander3
(#)b
(#)b
(#)b
(#)b
AL
81
2,008,103
16.6%
23.2%
0.5%
1.4%
0.1%
2.3%
5.7%
0
0
<1.0
6
<1.0
6
4.3
8
DC
2
632,323
14.3%
39.5%
0.2%
5.4%
0.1%
3.0%
9.9%
0
0
0
0
<1.0
1
<1.0
1
GA
14
643,252
20.1%
39.3%
0.3%
1.3%
0.0%
2.3%
8.8%
0
0
<1.0
2
<1.0
2
<1.0
2
IL
31
549,576
14.5%
16.8%
0.2%
1.6%
0.0%
2.4%
6.1%
0
0
1.4
7
1.4
7
1.4
7
IN
5
200,792
34.3%
33.5%
0.4%
0.1%
1.0%
4.4%
4.9%
0
0
2.0
3
2.0
3
2.0
3
KS
12
168,609
10.9%
7.2%
0.7%
1.3%
0.0%
3.1%
10.5%
0
0
2.6
4
2.6
4
2.6
4
KY
38
349,733
18.4%
5.4%
0.1%
0.6%
0.0%
1.9%
4.5%
0
0
0.7
5
0.7
5
0.8
5
LA
18
968,256
18.7%
40.0%
0.3%
3.2%
0.0%
2.0%
9.9%
0
0
3.7
9
3.7
9
3.8
9
MA
10
358,066
13.3%
3.8%
0.2%
9.5%
0.0%
1.9%
29.0%
1.1
6
1.1
6
1.1
6
1.1
6
MD
19
3,936,765
10.9%
39.0%
0.2%
8.0%
0.1%
3.2%
12.0%
0
0
0
0
0.1
1
0.1
1
MO
19
1,824,039
10.7%
23.0%
0.1%
3.7%
0.0%
2.5%
3.0%
0
0
0
0
12
11
12
11
NC
37
1,337,529
13.6%
57.9%
0.1%
2.0%
0.0%
2.5%
7.5%
0
0
0
0
<1.0
1
4.7
6
ND
11
33,052
7.6%
1.3%
3.3%
0.7%
0.0%
2.1%
3.2%
0
0
<1.0
1
<1.0
1
<1.0
1
NH
1
87,932
10.8%
3.0%
0.1%
7.6%
0.0%
2.9%
15.1%
<1.0
1
<1.0
1
<1.0
1
<1.0
1
OH
19
109,283
23.4%
6.1%
0.3%
1.0%
0.0%
2.9%
2.4%
0
0
<1.0
2
<1.0
2
<1.0
2
97
-------
Section 9—Distributional Analysis of Pollutant Exposures
Table 31. Modeled Changes in Total Excess Bladder Cancer Deaths Avoided Under the Regulatory Options
Among Potentially Affected Drinking Water Systems, by State
Percent
American
Indian/
Alaska
Native3
Percent
Native
Hawaiian/
Pacific
Islander3
Option 1
Option 2
Option 3
Option 4
State
# Potentially
Affected
PWS
Population
Served
Percent
Low-
Income3
Percent
African-
American3
Percent
Asian3
Percent
Other3
Percent
Hispanic/
Latino3
Deaths
Avoided
(#)b
PWS
(#)
Deaths
Avoided
(#)b
PWS
(#)
Deaths
Avoided
(#)b
PWS
(#)
Deaths
Avoided
(#)b
PWS
(#)
PA
68
3,598,707
12.0%
11.9%
0.1%
3.9%
0.0%
2.5%
5.7%
0
0
2.9
7
3.0
7
3.0
7
SC
43
473,094
13.0%
22.6%
0.5%
1.5%
0.1%
2.6%
4.8%
0
0
0
0
0
0
<1.0
2
SD
98
135,807
14.9%
1.0%
11.1%
1.9%
0.1%
2.1%
3.6%
0
0
<1.0
3
<1.0
3
<1.0
3
VA
35
3,090,649
7.5%
15.7%
0.2%
12.4%
0.1%
4.2%
14.5%
0
0
0
0
0
0
1.0
4
WV
21
256,821
19.6%
3.9%
0.1%
2.1%
0.0%
2.9%
2.3%
0
0
<1.0
1
<1.0
1
<1.05
2
Total
582
20,762,388
2.1
7
21.4
57
35.6
71
44.85
85
US
13.7%
12.2%
0.7%
5.4%
0.2%
2.7%
18.8%
Notes:
a) Socioeconomic characteristics are population-weighted to reflect differences in populations served by potentially affected PWS within each state, as well as characteristics of different ZCTAs
intersected by the PWS service areas. Each racial and ethnic category besides Hispanic or Latino represent the subset of the race and ethnicity that is identified as "non-Hispanic".
b) This column shows the total number of excess bladder cancer deaths avoided under each of the regulatory options over the period of analysis.
c) California and Nebraska had 105 PWS with very small cancer cases avoided that resulted in no deaths avoided for any regulatory option.
98
-------
Section 9—Distributional Analysis of Pollutant Exposures
The results of EPA's analysis showed that, across all states, all of the regulatory options result in increases
in excess bladder cancer deaths avoided (Table 31).
Under Option 1, increases in the number of excess bladder cancer deaths avoided are observed across
seven systems in two states-Massachusetts and New Hampshire (Table 31). Populations served by
potentially affected systems in Massachusetts have larger proportions of Asian (non-Hispanic) and
Hispanic or Latino people than the national average (Table 31). Additionally, populations served by
potentially affected systems in New Hampshire have larger proportions of Asian (non-Hispanic) and Other
(non-Hispanic) people than the national average (Table 31).
Option 2 results in increases in excess bladder cancer deaths avoided across 57 systems in 14 states
(Table 31). Of these 14 states, 13 have populations served by affected systems where the percent of the
population for at least one population group of concern is above the national average (Table 31). For
three states which have one population group of concern above the national average, the median change
in excess bladder cancer deaths avoided observed under Option 2 is about one death (Table 31). Across
nine states which have two population groups of concern above the national average, the median change
in excess bladder cancer deaths avoided observed under Option 2 is about one death (Table 31). Lastly,
for one state which has three or more population groups of concern above the national average, the
change in excess bladder cancer deaths avoided observed under Option 2 is about two deaths (Table 31).
Under Option 3, increases in excess bladder cancer deaths avoided are observed across 71 systems in 18
states (Table 31). Of these 18 states, 17 have populations served by affected systems where the percent
of the population for at least one population group of concern is above the national average (Table 31).
For five states which have one population group of concern above the national average, the median
change in excess bladder cancer deaths avoided observed under Option 3 is about one death (Table 31).
Across nine states which have two population groups of concern above the national average, the median
change in excess bladder cancer deaths avoided observed under Option 3 is about one death (Table 31).
Lastly, for three states which have three or more population groups of concern above the national
average, the median change in excess bladder cancer deaths avoided observed under Option 3 is about
one death (Table 31).
Option 4 results in increases in the number of excess bladder cancer deaths avoided across 85 systems in
all 20 states with potentially affected systems (Table 31). Of these states, 19 have populations served by
affected systems where the percent of the populations for at least one population group of concern is
above the national average (Table 31). For six states which have one population group of concern above
the national average, the median change in excess bladder cancer deaths avoided observed under Option
4 is about 1.8 deaths (Table 31). Across 10 states which have two population groups of concern above the
national average, the median change in excess bladder cancer deaths avoided observed under Option 4 is
about 1.03 deaths (Table 31). Finally, for three states which have three or more population groups of
concern above the national average, the median change in excess bladder cancer deaths avoided
observed under Option 4 is about one deaths (Table 31).
9.3.3 Key Conclusions
The results of EPA's analysis of changes in TTHM concentrations and resulting changes in bladder cancer
cases and deaths from consuming drinking water with TTHM, showed that, across all of the analyses, that
all of the regulatory options result in a decrease in TTHM concentrations and increases in bladder cancer
cases and excess bladder cancer deaths avoided in states with affected drinking water systems. Of the
regulatory options evaluated, across the analyses and states with affected systems, EPA concluded that
Option 4 generated the greatest improvements. Across the analyses, under each of the regulatory
options, the majority of states with affected systems served populations with at least one population
group of concern above the national average, with the largest proportion of these states having two
population groups of concern above the national average. Analyzing the distribution of changes across
the analyses and regulatory options, EPA found that states with affected systems serving populations with
one population group of concern above the national average experienced the largest median changes in
99
-------
Section 9—Distributional Analysis of Pollutant Exposures
TTHM concentrations and bladder cancer cases and excess bladder cancer deaths avoided than states
serving populations with two and three or more population groups of concern above the national
average, respectively. While the magnitude of the median change observed across the analyses
decreased with the more stringent regulatory options in communities with one, two, or three or more
population groups of concern above the national average, EPA found that this was not due to a there
being fewer reductions in TTHM concentrations and increases in bladder can cases and excess bladder
cancer deaths avoided with more stringent options, but rather that more new states with affected
systems experiencing smaller changes were being added under the more stringent options. Therefore,
EPA concluded that Option 4 still generated the greatest improvements. Given that the analysis focused
on changes under the regulatory options, EPA could not draw conclusions with respect to how the
magnitude and distribution of improvements under the regulatory options affects the baseline
distribution of exposures to TTHM and the incidence of bladder cancer cases and deaths among
population groups of concern.
9.4 Cumulative Risks
In previous Steam Electric EAs, EPA focused on assessing potential impacts to human health caused by
individual pollutants present in steam electric power plant wastewater discharges. As indicated by the
results of the human health effects in the immediate receiving water distributional analysis (Section 9.2),
communities can be exposed to multiple pollutants from steam electric power plant discharges, the
effects of which may not be fully captured when analyzing impacts on the basis of an individual pollutant.
Therefore, for the proposed rule, EPA expanded the individual pollutant assessment to include a further
evaluation of potential impacts to human health from mixtures of pollutants present in steam electric
power plant discharges.
To analyze the human health effects caused by exposures to multiple pollutants, EPA used a three-tiered
framework developed by the Agency for Toxic Substances and Disease Registry (ATSDR) for evaluating the
joint toxic action (JTA) of multiple pollutants. For more information on the methodology EPA used to
perform the JTA analysis, see the EPA memorandum Methodology for Assessing Human Health Impacts
from Multiple Pollutants in Steam Electric Power Plant Discharges (U.S. EPA, 2023g).
In Tier 1, potential human health impacts are evaluated for individual pollutants within a mixture using
the HQ44 method or by calculating a cancer risk estimate (CRE)45 (ATSDR, 2018). For more information on
the results of EPA's Tier 1 analysis, see the 2023 EA.
In Tier 2, individual pollutants with an HQ greater than or equal to 0.1 or a CRE greater than or equal to
10~6 are considered to pose a potential threat to human health and are retained for the Tier 2 analysis
(ATSDR, 2018).Given that arsenic was the only pollutant evaluated in the 2023 EA IRW human health
module with a published cancer slope factor, EPA did not perform a JTA analysis on potential cumulative
cancer risk from steam electric power plant discharges. Potential cumulative risks were only evaluated for
non-cancer human health effects. Next, a preliminary assessment is conducted for evaluating the
potential for JTA among multiple pollutants in a mixture. A preliminary Hazard Index (HI) is calculated as
the sum of the HQs for the remaining pollutants within a mixture. A preliminary HI greater than 1
indicates the potential for human health impacts caused by additive effects of the pollutants within the
mixture. Tier 3 further refines the assessment in Tier 2 to a specific health effect from a common mode of
action and duration. For more information on the results of EPA's Tier 2 analysis, see the 2023 EA.
44 HQs are calculated as the ratio of the exposure estimate to an established human health-based metric like an
ATSDR MRL or an EPA RfD value.
45, CREs are calculated as by multiplying the exposure estimate by and EPA cancer slope factor.
100
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Section 9—Distributional Analysis of Pollutant Exposures
In the Tier 3 analysis, benchmark values (i.e., RfD, minimal risk level [MRL], and target organ toxicity dose
[TTD]) established for similar health effects and modes of action are used46 to calculate human health
endpoint-specific HQ values. Endpoint specific values are then summed to calculate a human health
endpoint-specific HI value. A human health endpoint-specific HI greater than 1 indicates a potential
human health impact due to the assumption of dose additivity of the pollutants within the mixture
(ATSDR, 2004a). Lastly, ATSDR recommends using a qualitative binary weight-of-evidence (BINWOE)
assessment for evaluating interactions among pollutant pairs in a mixture. The results of the BINWOE
analysis provide an indication of the direction of a given interaction among pollutants and assigns
qualitative statements to the human health endpoint-specific HI like greater than additive, additive, less
than additive, and indeterminate. BINWOE factors for pollutant pairs included in the Tier 3 analysis are
summed to determine whether the potential for a health effect may be greater or less than what is
predicted based on the endpoint-specific HI alone. Positive combined BINWOE scores that are
significantly different than zero indicate that the mixture is likely to pose a greater hazard than indicated
by an HI alone. Negative combined BINWOE scores that are significantly different from zero suggest that
the mixture poses less of a hazard than indicated by the endpoint-specific HI alone. Combined BINWOE
scores of zero or close to zero indicate the endpoint-specific HI is a reasonable prediction of the potential
threat posed by the mixture (ATSDR, 2004a).
ATSDR has developed 12 final and three draft interaction profiles that describe the potential human
health effects ofJTAof pollutants in a mixture. Of these interaction profiles, EPA reviewed three for
incorporation into the analysis: Interaction Profile for Arsenic, Cadmium, Chromium, and Lead; Interaction
Profile for Lead, Manganese, Zinc, and Copper; and Interaction Profile for Chlorpyrifos, Lead, Mercury, and
Methylmercury (ATSDR, 2004b, 2004c, 2006). Based on human health effects module of the IRW Model
EPA used to assess human health effects from fish consumption in the EA, EPA identified five pollutants
for consideration in the JTA analysis: arsenic, cadmium, lead, zinc, and methylmercury. Using the health
endpoint-specific benchmarks included in the ATSDR interaction profiles, EPA identified five human
health effects to include in the JTA analysis: neurological, renal, cardiovascular, hematological, and
testicular.
The JTA analysis was performed at the immediate receiving water level under the baseline and each of
the regulatory options, the results of which are presented and discussed below. Included with the results
is information on the socioeconomic characteristics of communities with immediate receiving waters with
and without mixture- and health endpoint-specific HI exceedances under the baseline and regulatory
options. This was done to facilitate a distributional assessment of cumulative risks to determine whether
PEJC exist under the baseline and/or regulatory options.
9.4.1 Distribution of Cumulative Risks among Affected Communities
For the Tier 2 analysis, EPA calculated human health endpoint-specific HQ values for the five pollutants
previously discussed under the baseline and each of the four regulatory options. HQs were calculated for
each immediate receiving water and each consumer cohort group (child subsistence, child recreational,
adult subsistence, adult recreational). Immediate receiving waters with two or more pollutants where the
HQ from the Tier 2 analysis was greater than or equal to 0.1 are included in the Tier 3 analysis. As noted
earlier, EPA did not identify any immediate receiving waters where arsenic exceeded the HQ value of 0.1.
For the Tier 3 analysis, EPA calculated human health endpoint-specific HI values under the baseline and
each of the four regulatory options for three mixtures of concern identified from the Tier 2 results:
Arsenic-Cadmium-Lead (As-Cd-Pb), Zinc-Lead (Zn-Pb), and Methylmercury-Lead (MeHg-Pb). Within each
consumer cohort, HI values were calculated for each immediate receiving water where multiple
pollutants exceeded an HQ of 0.1. Information on the socioeconomic characteristics of communities with
46, A RfD or MRL value is used when the critical effect is equal to the human health effect being evaluated in the
hazard index. A TTD value is used when the pollutant is known to cause an effect of concern at a concentration
greater than the critical effect associated with the pollutant's RfD or MRL value (ATSDR, 2004a).
101
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Section 9—Distributional Analysis of Pollutant Exposures
affected immediate receiving waters was included to facilitate a distributional analysis of human health
impacts from exposures to multiple pollutants in steam electric power plant discharges. The results of the
analysis are presented in Table 32a-Table 32f.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32a. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Cardiovascular
Impacts Under Baseline and the Regulatory Options for Arsenic-Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
Baseline
Options 1 through 4
Demographics
National Average
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Child, Subsistence Fisher
Percent Low-Income
13.7%
1.1%
5.7%
Not applicable (NA)
5.7%
Percent African American
(non-Hispanic)
12.2%
0%
7.7%
NA
7.7%
Percent American
Indian/Alaska Native
0.7%
0%
1.3%
NA
1.3%
Percent Asian
5.4%
1.8%
2.0%
NA
2.0%
Percent Native
Hawaiian/Pacific Islander
0.2%
0%
0.1%
NA
0.1%
Percent Other (non-
Hispanic)
2.7%
0.4%
2.4%
NA
2.4%
Percent Hispanic/Latino
18.8%
0%
5.7%
NA
5.6%
Total Population
1,687
265,971
0
267,658
Count of IRW
1
97
0
98
Source: 2023 EA
Abbreviations: IRW (immediate receiving water); NA (not applicable).
a - EPA assessed human health impacts from the joint toxic action of multiple pollutants in steam electric power plant discharges, calculating a hazard index (HI) based on
individual pollutant hazard quotients to determine exceedances of HI > 1.0. See the 2023 EA for more details on the analysis.
b - Lead blood levels only available for child cohorts. No exceedances under baseline or the regulatory options for child (recreational), adult (recreational), or adult (subsistence)
fishers.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32b. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Hematological
Impacts Under Baseline and the Regulatory Options for Arsenic-Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
Baseline
Option 1
Options 2 through 4
Demographics
Average
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Child, Recreational Fisher
Percent Low-Income
13.7%
1.1%
5.7%
1.1%
5.7%
1.1%
5.7%
Percent African
American (non-
Hispanic)
12.2%
0%
7.7%
0%
7.7%
0%
7.7%
Percent American
Indian/Alaska Native
0.7%
0%
1.3%
0%
1.3%
0%
1.3%
Percent Asian
5.4%
1.8%
2.0%
1.8%
2.0%
1.8%
2.0%
Percent Native
Hawaiian/Pacific
Islander
0.2%
0%
0.1%
0%
0.1%
0%
0.1%
Percent Other (non-
Hispanic)
2.7%
0.4%
2.4%
0.4%
2.4%
0.4%
2.4%
Percent Hispanic/Latino
18.8%
0%
5.7%
0%
5.7%
0%
5.7%
Total Population
1,687
265,971
1,687
265,971
1,687
265,971
Count of IRW
1
97
1
97
1
97
Child, Subsistence Fisher
Percent Low-Income
13.7%
7.6%
5.6%
1.6%
5.8%
1.1%
5.7%
Percent African
American (non-
Hispanic)
12.2%
13.6%
7.3%
0%
7.7%
0%
7.7%
Percent American
Indian/Alaska Native
0.7%
0.2%
1.4%
0.6%
1.3%
0%
1.3%
Percent Asian
5.4%
1.9%
2.0%
1.0%
2.0%
1.8%
2.0%
Percent Native
Flawaiian/Pacific
Islander
0.2%
0.3%
0.1%
0%
0.1%
0%
0.1%
Percent Other (non-
H ispanic)
2.7%
3.4%
2.4%
3.0%
2.4%
0.4%
2.4%
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32b. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Hematological
Impacts Under Baseline and the Regulatory Options for Arsenic-Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
National
Average
Baseline
Option 1
Options 2 through 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Percent
Hispanic/Latino
18.8%
4.4%
5.7%
4.3%
5.6%
0%
5.7%
Total Population
16,060
251,598
3,008
264,650
1,687
265,971
Count of IRW
8
90
2
96
1
97
Source-. 2023 EA
Abbreviations: IRW (immediate receiving water).
a - EPA assessed human health impacts from the joint toxic action of multiple pollutants in steam electric power plant discharges, calculating a hazard index (HI) based on
individual pollutant hazard quotients to determine exceedances of HI > 1.0. See the 2023 EA for more details on the analysis.
b - Lead blood levels only available for child cohorts. No exceedances under baseline or the regulatory options for adult (recreational) or adult (subsistence) fishers.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32c. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Hematological
Impacts Under Baseline and the Regulatory Options for Zinc-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
Baseline
Options 1 through 4
Demographics
National Average
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Child, Subsistence Fisher
Percent Low-Income
13.7%
1.1%
5.7%
Not applicable (NA)
5.7%
Percent African American
(non-Hispanic)
12.2%
0%
7.7%
NA
7.7%
Percent American
Indian/Alaska Native
0.7%
0%
1.3%
NA
1.3%
Percent Asian
5.4%
1.8%
2.0%
NA
2.0%
Percent Native
Hawaiian/Pacific Islander
0.2%
0%
0.1%
NA
0.1%
Percent Other (non-
Hispanic)
2.7%
0.4%
2.4%
NA
2.4%
Percent Hispanic/Latino
18.8%
0%
5.7%
NA
5.6%
Total Population
1,687
265,971
0
267,658
Count of IRW
1
97
0
98
Source: 2023 EA
Abbreviations: IRW (immediate receiving water); NA (not applicable).
a - EPA assessed human health impacts from the joint toxic action of multiple pollutants in steam electric power plant discharges, calculating a hazard index (HI) based on
individual pollutant hazard quotients to determine exceedances of HI > 1.0. See the 2023 EAfor more details on the analysis.
b - Lead blood levels only available for child cohorts. Joint toxic action analysis limited to child (recreational) and child (subsistence) cohorts. No exceedances under baseline or
the regulatory options for child (recreational) fishers.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32d. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Neurological Impacts
Under Baseline and the Regulatory Options for Arsenic-Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
National
Average
Baseline
Option 1
Option 2
Options 3 and 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Child, Recreational Fisher
Percent Low-
Income
13.7%
6.4%
5.7%
8.1%
5.6%
9.2%
5.6%
9.2%
5.6%
Percent African
American (non-
12.2%
12.4%
7.2%
21.2%
7.2%
25.2%
7.2%
25.2%
7.2%
Hispanic)
Percent American
Indian/Alaska
0.7%
0.2%
1.4%
0.5%
1.3%
0.3%
1.3%
0.3%
1.3%
Native
Percent Asian
5.4%
1.5%
2.0%
0.8%
2.0%
0.9%
2.0%
0.9%
2.0%
Percent Native
Hawaiian/Pacific
0.2%
0.2%
0.1%
0.5%
0.1%
0.6%
0.1%
0.6%
0.1%
islander
Percent Other
(non-Hispanic)
2.7%
3.6%
2.3%
3.5%
2.4%
3.0%
2.4%
3.0%
2.4%
Percent
Hispanic/Latino
18.8%
3.8%
5.8%
5.4%
5.6%
4.5%
5.7%
4.5%
5.7%
Total Population
21,536
246,122
8,407
259,251
7,086
260,572
7,086
260,572
Count of IRW
10
88
3
95
2
96
2
96
Child, Subsistence Fisher
Percent Low-
Income
13.7%
6.9%
5.6%
7.0%
5.6%
7.0%
5.6%
6.5%
5.7%
Percent African
American (non-
12.2%
10.1%
7.3%
11.4%
7.3%
11.4%
7.3%
12.2%
7.2%
Hispanic)
Percent American
Indian/Alaska
0.7%
5.2%
0.8%
7.0%
0.8%
7.0%
0.8%
0.2%
1.4%
Native
Percent Asian
5.4%
1.3%
2.1%
1.4%
2.1%
1.4%
2.1%
1.5%
2.1%
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32d. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Neurological Impacts
Under Baseline and the Regulatory Options for Arsenic-Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
National
Average
Baseline
Option 1
Option 2
Options 3 and 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Percent Native
Hawaiian/Pacific
0.2%
0.1%
0.1%
0.2%
0.1%
0.2%
0.1%
0.2%
0.1%
Islander
Percent Other
(non-Hispanic)
2.7%
2.5%
2.4%
3.3%
2.3%
3.3%
2.3%
3.5%
2.3%
Percent
Hispanic/Latino
18.8%
6.2%
5.5%
3.7%
5.8%
3.7%
5.8%
3.8%
5.8%
Total Population
32,392
235,266
23,650
244,008
23,650
244,008
22,003
245,655
Count of IRW
15
83
12
86
12
86
11
87
Source: 2023 EA
Abbreviations: IRW (immediate receiving water).
a - EPA assessed human health impacts from the joint toxic action of multiple pollutants in steam electric power plant discharges, calculating a hazard index (HI) based on
individual pollutant hazard quotients to determine exceedances of HI > 1.0. See the 2023 EA for more details on the analysis.
b - Lead blood levels only available for child cohorts. No exceedances under baseline or the regulatory options for adult (recreational) or adult (subsistence) fishers.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32e. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Neurological Impacts
Under Baseline and the Regulatory Options for Methylmercury-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
National
Average
Baseline
Options 1 and 2
Options 3 and 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Child, Recreational Fisher
Percent Low-Income
13.7%
7.4%
5.4%
6.9%
5.5%
6.5%
5.6%
Percent African
American (non-
12.2%
9.1%
7.4%
9.9%
7.3%
10.6%
7.3%
Hispanic)
Percent American
Indian/Alaska Native
0.7%
4.0%
0.8%
5.1%
0.8%
0.2%
1.5%
Percent Asian
5.4%
1.1%
2.2%
1.3%
2.1%
1.3%
2.1%
Percent Native
Hawaiian/Pacific
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
islander
Percent Other (non-
Hispanic)
2.7%
2.1%
2.5%
2.5%
2.4%
2.6%
2.4%
Percent
Hispanic/Latino
18.8%
4.9%
5.8%
6.1%
5.6%
6.4%
5.5%
Total Population
42,822
224,836
32,957
234,701
30,745
236,913
Count of IRW
23
75
16
82
14
84
Child, Subsistence Fisher
Percent Low-Income
13.7%
6.9%
5.4%
7.0%
5.5%
6.5%
5.6%
Percent African
American (non-
12.2%
9.6%
7.2%
9.7%
7.3%
10.3%
7.3%
Hispanic)
Percent American
Indian/Alaska Native
0.7%
3.3%
0.8%
4.8%
0.8%
0.2%
1.5%
Percent Asian
5.4%
0.9%
2.3%
1.3%
2.1%
1.4%
2.1%
Percent Native
Hawaiian/Pacific
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Islander
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32e. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Neurological Impacts
Under Baseline and the Regulatory Options for Methylmercury-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
National
Average
Baseline
Options 1 and 2
Options 3 and 4
Demographics
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Exceedances
Percent Other (non-
Hispanic)
2.7%
1.8%
2.6%
2.4%
2.4%
2.5%
2.4%
Percent
Hispanic/Latino
18.8%
5.8%
5.6%
5.8%
5.6%
6.1%
5.6%
Total Population
56,069
211,589
35,026
232,632
32,814
234,844
Count of IRW
28
70
19
79
17
81
Source: 2023 EA
Abbreviations: IRW (immediate receiving water).
a - EPA assessed human health impacts from the joint toxic action of multiple pollutants in steam electric power plant discharges, calculating a hazard index (HI) based on
individual pollutant hazard quotients to determine exceedances of HI > 1.0. See the 2023 EAfor more details on the analysis,
b - Lead blood levels only available for child cohorts. Joint toxic action analysis limited to child (recreational) and child (subsistence) cohorts.
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Section 9—Distributional Analysis of Pollutant Exposures
Table 32f. Immediate Receiving Water Community Demographics by Joint Toxic Action Hazard Index Exceedances3 for Renal Impacts Under
Baseline and the Regulatory Options for Arsenic-Cadmium-Lead Mixtures, Organized by Age and Fishing Mode Cohortb
National
Average
Baseline
Options 1 and 2
Options 3 and 4
Demographics
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
IRW with
Exceedances
IRW without
Exceedances
Child, Subsistence Fisher
Percent Low-Income
13.7%
6.8%
5.7%
7.0%
5.6%
6.1%
5.7%
Percent African
American (non-
Hispanic)
12.2%
2.7%
8.0%
2.9%
7.9%
3.2%
7.9%
Percent American
Indian/Alaska Native
0.7%
10.4%
0.7%
11.6%
0.7%
0.2%
1.4%
Percent Asian
5.4%
1.7%
2.0%
1.9%
2.0%
2.2%
2.0%
Percent Native
Hawaiian/Pacific
Islander
0.2%
0%
0.1%
0%
0.1%
0%
0.1%
Percent Other (non-
Hispanic)
2.7%
2.9%
2.4%
3.2%
2.4%
3.5%
2.4%
Percent
Hispanic/Latino
18.8%
3.5%
5.8%
3.1%
5.8%
3.1%
5.7%
Total Population
15,765
251,893
14,090
253,568
12,443
255,215
Count of IRW
11
87
9
89
8
90
Source: 2023 EA
Abbreviations: IRW (immediate receiving water).
a - EPA assessed human health impacts from the joint toxic action of multiple pollutants in steam electric power plant discharges, calculating a hazard index (HI) based on
individual pollutant hazard quotients to determine exceedances of HI > 1.0. See the 2023 EAfor more details on the analysis.
b - Lead blood levels only available for child cohorts. No exceedances under baseline or the regulatory options for child (recreational), adult (recreational), or adult
(subsistence) fishers.
Ill
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Section 9—Distributional Analysis of Pollutant Exposures
Cardiovascular and Hematological (Zn-Pb Mixture) Human Health Impacts
Among child subsistence fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population group is less than the national average in
communities with immediate receiving waters with and without mixture-specific HI exceedances for
cardiovascular and hematological human health impacts (Table 32a and Table 32c). The one exception to
this occurs in communities wih immediate receiving waters without exceedances, where the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) is above the national
average (Table 32a and Table32c). Comparingthe percent of the population identified as low-income or a
racial or ethnic minority population group between communities with immediate receiving waters with
and without exceedances for cardiovascular and hematological human health impacts, the results of the
baseline analysis shows that communities with immediate receiving waters with exceedances have
smaller proportion of population groups of concern than the communities with immediate receiving
waters without exceedances (Table 32a and Table 32c).
The results of the analysis of the regulatory options show that, compared to the baseline, all options
results in no immediate receiving waters with mixture-specific HI exceedances for cardiovascular and
hematological human health impacts (Table 32a and 32c).
Hematological (As-Cd-Pb Mixture) Human Health Impacts
Among child recreational fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population group is less than the national average (Table 32b).
The one exception to this occurs in communities with immediate receiving waters without mixture-
specific HI exceedances for hematological human health impacts, where the percent of the population
identified as American Indian or Alaska Native (non-Hispanic) is above the national average (Table 32b).
When comparing the percent of the population identified as low-income or a racial and ethnic minority
population group between communities with immediate receiving waters with and without exceedances,
the results of the baseline analysis show that communities with immediate receiving waters with
exceedances have a smaller proportion of population groups of concern than communities with
immediate receiving waters without exceedances (Table 32b).
The results of the analysis of regulatory options show that none of the regulatory options result in a
change in the number and distribution of immediate receiving waters with exceedances under the
baseline (Table 32b).
Among child recreational fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population is less than the national average in communities
with immediate receiving waters with and without mixture-specific HI exceedances for hematological
human health impacts, except for African-American (non-Hispanic) and Other (non-Hispanic) populations
where exceedances are observed and American Indian or Alaska Native (non-Hispanic) populations where
no exceedances are observed (Table 32b). When comparing the percent of the population identified as
low-income or a racial and ethnic minority population group between communities with immediate
receiving waters with and without exceedances, the percent of the population identified as low-income,
African-American (non-Hispanic), and Other (non-Hispanic) is higher in communities with immediate
receiving waters with exceedances (Table 32b). Although, when comparing the populations identified as
low-income or a racial ethnic minority population group in absolute terms, the number of individuals in
these groups is higher in communities with immediate receiving waters without exceedances across all
the population groups of concern (Table 32b). This is due to the fact that, under the baseline, the majority
of immediate receiving waters do not have exceedances and the majority of the affected population lives
in those areas (Table 32b).
The analysis of regulatory options showed that, compared to the baseline, all of the regulatory options
reduced the amount of immediate receiving waters with mixture-specific HI exceedances for
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Section 9—Distributional Analysis of Pollutant Exposures
hematological health impacts and reduced the population affected by these exceedances. Options 3 and
4 would generate the largest improvements (Table 32b).
Compared to the baseline, Option 1 improves potential distributional disparities by reducing the
proportion of the population identified as Other (non-Hispanic) to below the national average in
communities with immediate receiving waters with exceedances (Table 32b). Additionally, when
compared to the baseline, Option 1 reduces the proportion of the population identifying as low-income
and African-American (non-Hispanic) in communities with immediate receiving waters with exceedances
so that they are less than the proportion of the population in communities with immediate receiving
waters without exceedances (Table 32b).
Relative to the baseline, across all population groups of concern, Options 2, 3, and 4 improve potential
distributional disparities by reducing the proportion of the population identified as a population group of
concern to below the national average in communities with immediate receiving waters with
exceedances (Table 32b). Additionally, across all population groups of concern, Options 2, 3, and 4
reduce the proportion of the population identified as a population group of concern in communities with
immediate receiving waters with exceedances so that they are less than in communities with immediate
receiving waters without exceedances (Table 32b).
Neurological (As-Cd-Pb Mixture) Human Health Impacts
Among child recreational fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population is less than the national average in communities
with immediate receiving waters with and without mixture-specific HI exceedances for neurological
human health impacts, except for African-American (non-Hispanic) and Other (non-Hispanic) populations
where exceedances are observed and American Indian or Alaska Native (non-Hispanic) populations where
no exceedances are observed (Table 32d). When comparing the percent of the population identified as
low-income or a racial and ethnic minority population group between communities with immediate
receiving waters with and without exceedances, the percent of the population identified as low-income,
African-American (non-Hispanic), and Other (non-Hispanic) is higher in communities with immediate
receiving waters with exceedances (Table 32d). Although, when comparing the populations identified as
low-income or a racial ethnic minority population group in absolute terms, the number of individuals in
these groups is higher in communities with immediate receiving waters without exceedances across all
the population groups of concern (Table 32d). This is due to the fact that, under the baseline, the majority
of immediate receiving waters do not have exceedances and the majority of the affected population lives
in those areas (Table 32d).
The analysis of regulatory options showed that, compared to the baseline, all of the regulatory options
reduced the number of immediate receiving waters with mixture-specific HI exceedances for neurological
human health impacts and reduced the population affected by these exceedances (Table 32d). Although,
all of the regulatory options do not improve the distribution of population groups of concern in
communities with immediate receiving waters with exceedances (Table 32d).
Compared to the baseline, Options 1 through 4 do not improve potential distributional disparities as the
percent of the population identified as African-American (non-Hispanic) and Other (non-Hispanic) remain
above the national average in communities with immediate receiving waters with exceedances
(Table 32d). Additionally, relative to the baseline, under the regulatory options, the percent of the
population identified as Native Hawaiian or Pacific Islander (non-Hispanic) increases to above the national
average (Table 32d). Comparing the distribution of population groups of concern between communities
with immediate receiving waters with and without exceedances, Options 1 through 4 maintain the
baseline distribution, with the percent of the population identifying as low-income, African-American
(non-Hispanic), Other (non-Hispanic) being larger in communities with immediate receiving waters with
exceedances (Table 32d). In particular, the percent of the population identifying as African-American
(non-Hispanic) in communities with immediate receiving waters with exceedances almost doubles
compared to the baseline under Options 1 through 4 (Table 32d). Given that all the regulatory options
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result in a reduction in the number of immediate receiving waters with exceedances and the population
affected by these exceedances, the increase in the proportion of the African-American (non-Hispanic)
individuals relative to the baseline is likely due to the remaining communities with immediate receiving
waters with exceedances have small populations with high concentrations of African-American (non-
Hispanic) individuals (Table 32d).
Among child subsistence fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population is less than the national average in communities
with immediate receiving waters with and without mixture-specific HI exceedances for neurological
human health impacts, except for American Indian or Alaska Native (non-Hispanic) populations where
exceedances and no exceedances are observed (Table 32d). When comparing the percent of the
population identified as low-income or a racial and ethnic minority population group between
communities with immediate receiving waters with and without exceedances, the percent of the
population identified as low-income, African-American (non-Hispanic), American Indian or Alaska Native
(non-Hispanic), Other (non-Hispanic), and Hispanic or Latino is greater in communities with immediate
receiving waters with exceedances (Table 32d). Although, when comparing the populations identified as
low-income or a racial ethnic minority population group in absolute terms, the number of individuals in
these groups is higher in communities with immediate receiving waters without exceedances across all
the population groups of concern (Table 32d). This is due to the fact that, under the baseline, the majority
of immediate receiving waters do not have exceedances and the majority of the affected population lives
in those areas (Table 32d).
The analysis of regulatory options showed that, compared to the baseline, all of the regulatory options
reduced the number of immediate receiving waters with mixture-specific HI exceedances for neurological
human health impacts and reduced the population affected by these exceedances (Table 32d). Options 3
and 4 would generate the greatest improvements (Table 32d).
Compared to the baseline, Options 1 and 2 do not improve potential distributional disparities as the
percent of the population identified as American Indian or Alaska Native (non-Hispanic) remains above
the national average in communities with immediate receiving waters with exceedances (Table 32d).
Additionally, relative to the baseline, under Options 1 and 2, the percent of the population identified as
Other (non-Hispanic) increases to above the national average (Table 32d). Comparing the distribution of
population groups of concern between communities with immediate receiving waters with and without
exceedances, Options 1 and 2 improve the baseline distribution, as the percent of the population
identifying as Hispanic or Latino in communities with immediate receiving waters with exceedances falls
below the proportion in communities with immediate receiving waters without exceedances (Table 32d).
Relative to the baseline, Options 3 and 4 improve potential distributional disparities as the percent of the
population identified as American Indian or Alaska Native (non-Hispanic) decreases to below the national
average in communities with immediate receiving waters with exceedances (Table 32d). Although, the
percent of the population identified as Other (non-Hispanic) increases to above the national averages in
these communities (Table 32d). Comparing the distribution of population groups of concern between
communities with immediate receiving waters with and without exceedances, Options 3 and 4 improve
the baseline distribution, as the percent of the population identifying as American Indian or Alaska Native
(non-Hispanic) and Hispanic or Latino in communities with immediate receiving waters with exceedances
falls below the proportion in communities with immediate receiving waters without exceedances
(Table 32d).
Neurological (MeHg-Pb Mixture) Human Health Impacts
Among child recreational fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population is less than the national average in communities
with immediate receiving waters with and without mixture-specific HI exceedances for neurological
human health impacts, except for American Indian or Alaska Native (non-Hispanic) populations where
exceedances and no exceedances are observed (Table 32e). When comparing the percent of the
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population identified as low-income or a racial and ethnic minority population group between
communities with immediate receiving waters with and without exceedances, the percent of the
population identified as low-income, African-American (non-Hispanic), and American Indian or Alaska
Native (non-Hispanic) is greater in communities with immediate receiving waters with exceedances
(Table 32e). Although, when comparing the populations identified as low-income or a racial ethnic
minority population group in absolute terms, the number of individuals in these groups is higher in
communities with immediate receiving waters without exceedances across all the population groups of
concern (Table 32e). This is due to the fact that, under the baseline, the majority of immediate receiving
waters do not have exceedances and the majority of the affected population lives in those areas
(Table 32e).
The analysis of regulatory options showed that, compared to the baseline, all of the regulatory options
reduced the number of immediate receiving waters with mixture-specific HI exceedances for neurological
human health impacts and reduced the population affected by these exceedances (Table 32e). Options 3
and 4 would generate the greatest improvements (Table 32e).
Options 1 and 2 maintain the baseline distribution of population groups of concern relative the national
average (Table 32e). Comparing the distribution of population groups of concern between communities
with immediate receiving waters with and without exceedances, Options 1 and 2 do not improve the
baseline distribution, as the percent of the population identifying as low-income, African-American (non-
Hispanic), and American Indian or Alaska Native (non-Hispanic) in communities with immediate receiving
waters with exceedances remains greater than the proportion in communities with immediate receiving
waters without exceedances (Table 32e). Additionally, compared to the baseline, the percent of the
population identified as Other (non-Hispanic) and Hispanic or Latino increases in communities with
immediate receiving waters with exceedances to be greater than the proportion in communities with
immediate receiving waters without exceedances (Table 32e). Given that Options 1 and 2 result in a
reduction in the number of immediate receiving waters with exceedances and the population affected by
these exceedances, the increase in the proportion of the Other (non-Hispanic) and Hispanic or Latino
individuals relative to the baseline is likely due to the remaining communities with immediate receiving
waters with exceedances have small populations with high concentrations of these population groups
(Table 32e).
Compared to the baseline, Options 3 and 4 improve the potential distributional disparities as the percent
of the population identified as American Indian or Alaska Native (non-Hispanic) decreases to below the
national average in communities with immediate receiving waters with exceedances (Table 32e).
Comparing the distribution of population groups of concern between communities with immediate
receiving waters with and without exceedances, Options 3 and 4 improve the baseline distribution as the
percent of the population identifying as American Indian or Alaska Native (non-Hispanic) in communities
with immediate receiving waters with exceedances falls below the proportion in communities with
immediate receiving waters without exceedances (Table 32e). Although, under Options 3 and 4, the
percent of the population identified as Other (non-Hispanic) and Hispanic or Latino increases in
communities with immediate receiving waters with exceedances to be greater than the proportion in
communities with immediate receiving waters without exceedances (Table 32e). Given that Options 3 and
4 result in a reduction in the number of immediate receiving waters with exceedances and the population
affected by these exceedances, the increase in the proportion of the Other (no-Hispanic) and Hispanic or
Latino individuals relative to the baseline is likely due to the remaining communities with immediate
receiving waters with exceedances have small populations with high concentrations of these population
groups (Table 32e).
Among child subsistence fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population is less than the national average in communities
with immediate receiving waters with and without mixture-specific HI exceedances for neurological
human health impacts, except for American Indian or Alaska Native (non-Hispanic) populations where
exceedances and no exceedances are observed (Table 32e). When comparing the percent of the
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population identified as low-income or a racial and ethnic minority population group between
communities with immediate receiving waters with and without exceedances, the percent of the
population identified as low-income, African-American (non-Hispanic), American Indian or Alaska Native
(non-Hispanic), and Hispanic or Latino is greater in communities with immediate receiving waters with
exceedances (Table 32e). Although, when comparing the populations identified as low-income or a racial
ethnic minority population group in absolute terms, the number of individuals in these groups is higher in
communities with immediate receiving waters without exceedances across all the population groups of
concern (Table 32e). This is due to the fact that, under the baseline, the majority of immediate receiving
waters do not have exceedances and the majority of the affected population lives in those areas (Table
32e).
The analysis of regulatory options showed that, compared to the baseline, all of the regulatory options
reduced the number of immediate receiving waters with mixture-specific HI exceedances for neurological
human health impacts and reduced the population affected by these exceedances (Table 32e). Options 3
and 4 would generate the greatest improvements (Table 32e).
Options 1 and 2 maintain the baseline distribution of population groups of concern relative the national
average (Table 32e). Comparing the distribution of population groups of concern between communities
with immediate receiving waters with and without exceedances, Options 1 and 2 also maintain the
baseline distribution (Table 32e).
Compared to the baseline, Options 3 and 4 improve the potential distributional disparities as the percent
of the population identified as American Indian or Alaska Native (non-Hispanic) decreases to below the
national average in communities with immediate receiving waters with exceedances (Table 32e).
Comparing the distribution of population groups of concern between communities with immediate
receiving waters with and without exceedances, Options 3 and 4 improve the baseline distribution as the
percent of the population identifying as American Indian or Alaska Native (non-Hispanic) in communities
with immediate receiving waters with exceedances falls below the proportion in communities with
immediate receiving waters without exceedances (Table 32e). Although, under Options 3 and 4, the
percent of the population identified as Other (non-Hispanic) increases in communities with immediate
receiving waters with exceedances to be greater than the proportion in communities with immediate
receiving waters without exceedances (Table 32e). Given that Options 3 and 4 result in a reduction in the
number of immediate receiving waters with exceedances and the population affected by these
exceedances, the increase in the proportion of the Other (no-Hispanic) individuals relative to the baseline
is likely due to the remaining communities with immediate receiving waters with exceedances have small
populations with high concentrations of these population groups (Table 32e).
Renal (As-Cd-Pb Mixture) Human Health Impacts
Among child subsistence fish consumers, under the baseline, the percent of the population identified as
low-income or a racial and ethnic minority population is less than the national average in communities
with immediate receiving waters with and without mixture-specific HI exceedances for renal human
health impacts, except for American Indian or Alaska Native (non-Hispanic) and Other (non-Hispanic)
populations where exceedances are observed (Table 32f). When comparing the percent of the population
identified as low-income or a racial and ethnic minority population group between communities with
immediate receiving waters with and without exceedances, the percent of the population identified as
low-income, American Indian or Alaska Native (non-Hispanic), and Other (non-Hispanic) is greater in
communities with immediate receiving waters with exceedances (Table 32f). Although, when comparing
the populations identified as low-income or a racial ethnic minority population group in absolute terms,
the number of individuals in these groups is higher in communities with immediate receiving waters
without exceedances across all the population groups of concern (Table 32f). This is due to the fact that,
under the baseline, the majority of immediate receiving waters do not have exceedances and the
majority of the affected population lives in those areas (Table 32f).
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The analysis of regulatory options showed that, compared to the baseline, all of the regulatory options
reduced the number of immediate receiving waters with mixture-specific HI exceedances for neurological
human health impacts and reduced the population affected by these exceedances (Table 32f). Options 3
and 4 would generate the greatest improvements (Table 32f).
Options 1 and 2 maintain the baseline distribution of population groups of concern relative the national
average (Table 32f). Comparing the distribution of population groups of concern between communities
with immediate receiving waters with and without exceedances, Options 1 and 2 also maintain the
baseline distribution (Table 32f).
Compared to the baseline, Options 3 and 4 improve the potential distributional disparities as the percent
of the population identified as American Indian or Alaska Native (non-Hispanic) decreases to below the
national average in communities with immediate receiving waters with exceedances (Table 32f).
Comparing the distribution of population groups of concern between communities with immediate
receiving waters with and without exceedances, Options 3 and 4 improve the baseline distribution as the
percent of the population identifying as American Indian or Alaska Native (non-Hispanic) in communities
with immediate receiving waters with exceedances falls below the proportion in communities with
immediate receiving waters without exceedances (Table 32f). Although, under Options 3 and 4, the
percent of the population identified as Asian (non-Hispanic) increases in communities with immediate
receiving waters with exceedances to be greater than the proportion in communities with immediate
receiving waters without exceedances (Table 32f). Given that Options 3 and 4 result in a reduction in the
number of immediate receiving waters with exceedances and the population affected by these
exceedances, the increase in the proportion of the Asian (non-Hispanic) individuals relative to the
baseline is likely due to the remaining communities with immediate receiving waters with exceedances
have small populations with high concentrations of these population groups (Table 32f).
9.4.2 Key Conclusions
Based on the results of the distributional analysis of cumulative risks associated with exposures to
multiple pollutants discharged from steam electric power plants, EPA found that, across mixtures of
concern and fish consumers, under the baseline PEJC were observed largely among affected American
Indian or Alaska Native (non-Hispanic) populations when comparing the percent of the population
affected in communities with immediate receiving waters with mixture-specific HI exceedances for
relevant human health endpoints to the national average. Making an internal comparison between the
affected population, EPA found PEJC among specific population groups of concern as they comprised a
larger proportion of the population in communities with immediate receiving waters with exceedances
than in communities with immediate receiving waters without non-cancer and cancer exceedances.
Analyzing the regulatory options, EPA found that, across mixtures of concern and fish consumers, Options
3 and 4 most often generated the largest reductions in immediate receiving waters with non-cancer and
cancer exceedances and the population affected by these exceedances. EPA also found that, across
mixtures of concern and fish consumers, Options 3 and 4 most often produced the greatest
improvements in the distribution of impacts across the population groups of concern relative to the
baseline. Given this, EPA concluded that the regulatory options, particularly Options 3 and 4, reduce
exceedances in immediate receiving waters and the population affected by these exceedances, as well as
mitigate some of the PEJC observed under the baseline in terms of the distribution of population groups
of concern in communities with immediate receiving waters with exceedances relative to the average
community in the United States and to communities with immediate receiving waters without
exceedances.
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10. Distributional Analysis of Benefits and Costs of the
Proposed Rule
EPA examined the benefits and costs of the regulatory options in this proposal for potential disparities, in
addition to evaluating the distribution of exposures and health impacts discussed above. Office of
Management and Budget (OMB) Circular A-4 (2003), which implements E.O. 12866 (58 FR 51735
September 30, 1993), states that regulatory analyses "should provide a separate description of
distributional effects [i.e., how both benefits and costs are distributed among sub-populations of
particular concern)" As discussed below, EPA research demonstrates that climate change impacts
disparately accrue to minority and low-income populations, but evaluation of other benefits and costs
under the proposed rule may not have substantial impacts.
10.1 Benefits
EPA began its evaluation of benefits with a screening of the benefit categories. For Option 3 at both three
percent and seven percent discount rates, approximately 99 percent of benefits accrued from reductions
in air pollution due to estimated shifts in electric generation resulting from the incremental costs of the
proposed rule. Furthermore, these air benefits were always comprised of approximately a 3-to-l ratio of
conventional air pollutants health benefits to greenhouse gas (GHG) benefits. Thus, while EPA evaluated a
number of exposures and endpoints for disproportionate impacts, as discussed above, for purposes of
evaluating benefits, the Agency screened these two benefit categories through this initial comparison for
further evaluation.47
10.1.1 GHG Benefits
In 2009, under the Endangerment and Cause or Contribute Findings for Greenhouse Gases Under Section
202(a) of the Clean Air Act ("Endangerment Finding"), the Administrator considered how climate change
threatens the health and welfare of the U.S. population (U.S. EPA, 2009). As part of that consideration,
she also considered risks to minority and low-income individuals and communities, finding that certain
parts of the U.S. population may be especially vulnerable based on their characteristics or circumstances.
These groups include economically and socially disadvantaged communities; individuals at vulnerable
lifestages, such as the elderly, the very young, and pregnant or nursing women; those already in poor
health or with comorbidities; the disabled; those experiencing homelessness, mental illness, or substance
abuse; and/or Indigenous or minority populations dependent on one or limited resources for subsistence
due to factors including but not limited to geography, access, and mobility.
Scientific assessment and agency reports produced over the past decade by the United States Global
Change Research Program (USGCRP), the Intergovernmental Panel on Climate Change (IPCC), and the
National Academies of Science, Engineering, and Medicine (NASEM) add more evidence that the impacts
of climate change raise PEJC (USGCRP, 2018; USGCRP, 2016; Oppenheimer et al., 2014; Porter et al.,
2014; Smith et al., 2014; IPCC, 2018; National Research Council, 2011; NASEM, 2017). These reports
conclude that poorer or predominantly non-White communities can be especially vulnerable to climate
change impacts because they tend to have limited adaptive capacities and are more dependent on
climate-sensitive resources such as local water and food supplies or have less access to social and
information resources. Some communities of color, specifically populations defined jointly by
ethnic/racial characteristics and geographic location, may be uniquely vulnerable to climate change
health impacts in the United States. In particular, the 2016 scientific assessment on the Impacts of
47, EPA acknowledges that while the screening of benefits under Option 3 showed that nearly all the benefits
associated with the regulatory option can be attributed to benefits from reductions in air pollution, benefits
associated with other potential impacts from the rule that EPA did not quantify, like changes in housing prices,
could also have distributional impacts across affected populations.
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Climate Change on Human Health found with high confidence that vulnerabilities are place-and time-
specific, lifestages and ages are linked to immediate and future health impacts, and social determinants
of health are linked to greater extent and severity of climate change-related health impacts.
10.1.1.1 Effects on Specific Populations of Concern
Socioeconomic and educational factors affect the likelihood of an individual being exposed to negative
impacts of climate change. Individuals living in socially and economically disadvantaged communities,
such as those living at or below the poverty line or who are experiencing homelessness or social isolation,
are at greater risk of health effects from climate change. This is also true with respect to people at
vulnerable lifestages, specifically women who are pre-and perinatal, or are nursing; in utero fetuses;
children at all stages of development; and the elderly. Per the Fourth National Climate Assessment
(NCA4), "Climate change affects human health by altering exposures to heat waves, floods, droughts, and
other extreme events; vector-, food-and waterborne infectious diseases; changes in the quality and safety
of air, food, and water; and stresses to mental health and well-being" (Ebi et al., 2018). Many health
conditions such as cardiovascular or respiratory illness and other health impacts are associated with and
exacerbated by an increase in GHGs and climate change outcomes, which is problematic as these
diseases occur at higher rates within vulnerable communities. Importantly, negative public health
outcomes include those that are physical in nature, as well as mental, emotional, social, and economic.
To this end, as well, the scientific assessment literature-including the aforementioned USGCRP, IPCC, and
NASEM reports-demonstrates that there are myriad ways in which these populations may be affected at
the individual and community levels. Individuals face differential exposure to criteria pollutants, in part
due to the proximities of highways, trains, factories, and other major sources of pollutant-emitting
sources to less-affluent residential areas. Outdoor workers, such as construction or utility crews and
agricultural laborers, who frequently are comprised of already at-risk groups, are exposed to poor air
quality and extreme temperatures without relief. U.S. EPA (2021c) projected that individuals who are low-
income or who do not have a high school diploma are 25 percent more likely to live in areas with the
greatest losses of labor hours due to extreme temperatures. Low-income individuals or those without
high school diplomas are 15 percent more likely to live in areas that are projected to see the greatest
increases in childhood asthma diagnoses, due to climate change-driven increases to particulate air
pollution. Furthermore, individuals within populations of concern face greater housing, clean water, and
food insecurity and bear disproportionate economic impacts and health burdens associated with climate
change effects. They have less or limited access to healthcare and affordable, adequate health or
homeowner insurance. Finally, resiliency and adaptation are more difficult for economically
disadvantaged communities: They have less liquidity, individually and collectively, to move or to make the
types of infrastructure or policy changes to limit or reduce the hazards they face. They frequently are less
able to self-advocate for resources that would otherwise aid in building resilience and hazard reduction
and mitigation. Further findings of U.S. EPA (2021c) include findings that the following groups are more
likely than their reference population to currently live in areas with:
• The highest increases in childhood asthma diagnoses from climate-driven changes in PM2.5 (low-
income, Black and African American, Hispanic and Latino, and Asian populations);
• The highest percentage of land lost to inundation (low-income, American Indian and Alaska Native
populations);
• The highest increases in mortality rates due to climate-driven changes in extreme temperatures (low-
income and Black and African American populations);
• The highest rates of labor hour losses for weather-exposed workers due to extreme temperatures
(low-income, Black and African American, American Indian and Alaska Native, Hispanic and Latino,
and Pacific Islander populations);
• The highest increases in traffic delays associated with high-tide flooding (low-income, Hispanic and
Latino, Asian, and Pacific Islander populations); and
• The highest damages from inland flooding (Pacific Islanders populations).
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It is important to examine ways in which socially and physiologically vulnerable groups are exposed to and
experience threats posed by climate change. The assessment literature cited in EPA's 2009 and 2016
Endangerment Findings, as well as Impacts of Climate Change on Human Health (USGCRP, 2016),
concluded that certain populations and life stages, including children and older individuals, are more
vulnerable to climate-related health effects. The assessment literature produced from 2016 to the
present strengthens these conclusions by providing more detailed findings regarding related
vulnerabilities and the projected impacts youth may experience. These assessments-including the NCA4
(Ebi et al., 2018) and The Impacts of Climate Change on Human Health in the United States (USGCRP,
2016)-describe how children's unique physiological and developmental factors contribute to making
them particularly vulnerable to climate change. Impacts to children are expected from heat waves, air
pollution, infectious and waterborne illnesses, and mental health effects resulting from extreme weather
events. In addition, children are among those especially susceptible to allergens, as well as health effects
associated with heat waves, storms, and floods. Additional health concerns may arise in low-income
households, especially those with children, if climate change reduces food availability and increases
prices, leading to food insecurity within households.
Present research demonstrates that exposures and vulnerabilities to climate change impacts are a
product of a complex set of racial, ethnic, and age demographics; and geographic, sociocultural, and
economic factors. Individuals may experience hazards in aggregate or individually; they also may have
one, some, or multiple of the vulnerabilities considered. The Impacts of Climate Change on Human Health
(USGCRP, 2016) found that some communities of color, low-income groups, people with limited English
proficiency, and certain immigrant groups (especially those who are undocumented) live with many of
the factors that contribute to their vulnerability to the health impacts of climate change. While difficult to
isolate from related socioeconomic factors, race appears to be an important factor in vulnerability to
climate-related stress, with elevated risks for mortality from high temperatures reported for Black or
African American individuals compared to White individuals after controlling for factors such as air
conditioning use. Some research has found that race or ethnicity alone, more than other individual
demographic and socioeconomic characteristics, may play a significant role in determining one's risk of
experiencing harm as a result of climate change. This includes estimates that Black Americans are 40
percent more likely than non-Black individuals to live in areas of the U.S. experiencing the highest
projected increases in mortality rates due to changes in extreme temperatures (under a scenario of 2°C of
global warming). Additionally, Hispanic and Latino individuals in weather-exposed industries were found
to be 43 percent more likely to currently live in areas with the highest projected labor hour losses due to
extreme temperatures (U.S. EPA, 2021c). Moreover, people of color are disproportionately exposed to air
pollution based on where they live, and disproportionately vulnerable due to higher baseline prevalence
of underlying diseases such as asthma, so climate exacerbations of air pollution are expected to have
disproportionate effects on these communities.
Indeed, Native American Tribal communities possess unique vulnerabilities to climate change, particularly
those impacted by degradation of natural and cultural resources within established reservation
boundaries and threats to traditional subsistence lifestyles. Tribal communities whose health, economic
well-being, and cultural traditions depend upon the natural environment will likely be affected by the
degradation of ecosystem goods and services associated with climate change. The EPA found that
American Indian and Alaska Native individuals are 48 percent more likely than individuals not identifying
as such to currently live in areas where the highest percentage of land is projected to be inundated due
to sea level rise (under a scenario of 50cm of global sea level rise). Asian-Americans are 23 percent more
likely to live in coastal areas projected to see the highest increases in traffic delays due to high-tide
flooding on roadways (U.S. EPA, 2021c). The Fifth Assessment Report of the Intergovernmental Panel on
Climate Change (IPCC AR5) indicates that losses of customs and historical knowledge may cause
communities to be less resilient or adaptable (Porter et al., 2014). The NCA4 noted that while Indigenous
peoples are diverse and will be impacted by the climate changes universal to all Americans, there are
several ways in which climate change uniquely threatens Indigenous peoples' livelihoods and economies
(Jantarasami et al., 2018).
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In addition, there can institutional barriers to their management of water, land, and other natural
resources that could impede adaptive measures. For example, Indigenous agriculture in the Southwest is
already being adversely affected by changing patterns of flooding, drought, dust storms, and rising
temperatures leading to increased soil erosion, irrigation water demand, and decreased crop quality and
herd sizes. The Confederated Tribes of the Umatilla Indian Reservation in the Northwest have identified
climate risks to salmon, elk, deer, roots, and huckleberry habitat. Housing and sanitary water supply
infrastructure are vulnerable to disruption from extreme precipitation events.
The NCA4 noted that Indigenous peoples often have disproportionately higher rates of asthma,
cardiovascular disease, Alzheimer's, diabetes, and obesity, which can all contribute to increased
vulnerability to climate-driven extreme heat and air pollution events (Jantarasami et al., 2018). These
factors also may be exacerbated by stressful situations, such as extreme weather events, wildfires, and
other circumstances (Jantarasami et al., 2018).
The NCA4 and IPCC AR5 also highlighted several impacts specific to Alaska Indigenous Peoples
(Jantarasami et al., 2018; Porter et al., 2014). Coastal erosion and permafrost thaw will lead to more
coastal erosion, exacerbated risks of winter travel, and damage to buildings, roads, and other
infrastructure-these impacts on archaeological sites, structures, and objects that will lead to a loss of
cultural heritage for Alaska's Indigenous people. In terms of food security, the NCA4 discussed reductions
in suitable ice conditions for hunting, warmer temperatures impairing the use of traditional ice cellars for
food storage, and declining shellfish populations due to warming and acidification (Jantarasami et al.,
2018). While the NCA4 also noted that climate change provided more opportunity to hunt from boats
later in the fall season or earlier in the spring, the assessment found that the net impact was an overall
decrease in food security (Jantarasami et al., 2018).
In addition, the U.S. Pacific Islands and the indigenous communities that live there are also uniquely
vulnerable to the effects of climate change due to their remote location and geographic isolation. They
rely on the land, ocean, and natural resources for their livelihoods, but face challenges in obtaining
energy and food supplies that need to be shipped in at high costs. As a result, they face higher energy
costs than the rest of the nation and depend on imported fossil fuels for electricity generation and diesel.
These challenges exacerbate the climate impacts that the Pacific Islands are experiencing. The NCA4
notes that Indigenous peoples of the Pacific are threatened by rising sea levels, diminishing freshwater
availability, and negative effects to ecosystem services that threaten these individuals' health and well-
being (Jantarasami et al., 2018).
EPA notes that the changes in GHGs attributable to the regulatory options are small compared to
worldwide emissions. Nevertheless, the overall findings of these above-mentioned peer-reviewed
evaluations demonstrate that actions that reduce GHG emissions are likely to reduce impacts on
vulnerable communities, including minority and low-income populations
10.1.2 Conventional Air Pollutant Health Benefits
The current EPA modeling methodology for conventional air pollutants results in benefits that are
proportional to exposures. In other words, the distributional findings of air pollutant exposures discussed
above are the same findings EPA has for this benefit category: exposure and health benefit improvements
and degradations attributable to this proposal will be proportionately experienced by all demographic
populations evaluated. However, there are several important nuances and caveats to this conclusion
owing to differences in vulnerability and health outcomes across population subgroups. For example,
there is some information suggesting that the same PM2.5 exposure reduction will reduce the hazard of
mortality more so in Black populations than in White populations (U.S. EPA, 2019b; U.S. EPA, 2022f). In
addition, demographic-stratified information relating PM2.5 and ozone to other health effects and
valuation estimates is currently lacking.
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10.2 Costs
Energy provides many services to households that are necessary for a basic standard of living. The
proposed regulatory requirements will obligate steam electric plants to incur costs to install effluent
controls, which may impact the supply and prices of electricity, specifically residential electricity. This
section discusses how consumers can be affected by potential energy market impacts and characterizes
how energy burdens vary across the income distribution and for different racial/ethnic groups. The goal
of this section is to highlight which populations and communities may be most vulnerable to potential
energy market effects caused by regulatory impacts on the steam electric power sector. In addressing
these vulnerabilities, energy poverty, insecurity, and access are important concepts in the discussion of
energy burden. Energy insecurity is when households lack certainty that they will be able to afford their
energy bills. Energy poverty is when households lack sufficient energy to meet their needs. Finally, energy
access barriers are present when households lack access to affordable, reliable energy.
Energy poverty, insecurity, and access barriers are persistent problems facing many households across
the U.S.. Low-income and minority households are particularly vulnerable when energy prices increase.
Although these households consume less energy, it tends to represent a larger share of their budgets.
Drehobl, Ross, and Ayala (2020) find that low-income, Black, Hispanic, Native American, and older adult
households have disproportionally higher energy burdens than the average household. Lyubich (2020)
finds that Black households spend more on residential energy than White households after controlling for
income, household size, city, and homeowner status. Reames (2016) finds that home heating energy
efficiency is lower for census blocks in Kansas City, Missouri with a greater percentage of households in
poverty, higher percentage of minority head-of-household, lower median incomes, and a higher share of
adults without a high school diploma. He attributes the higher fuel poverty vulnerability among Black and
Hispanic households to racial segregation.
To investigate potential distributional impacts of higher electricity and fuel prices, EPA collected 2019
expenditure and income data stratified by pre-tax income quintiles and race from the Consumer
Expenditure Survey (CES) from the U.S. Bureau of Labor Statistics. EPA combined expenditures in the
following four categories to approximate "energy expenditures": (1) Natural gas, (2) Electricity, (3) Fuel oil
and other fuels, and (4) Gasoline, other fuels, and motor oil (transportation). The first three categories
are residential energy expenditures and the fourth category represents transportation energy
expenditures. These categories are assumed to potentially experience price impacts due to regulatory
costs affecting the steam electric power sector, though EPA expects impacts to be minimal. EPA examines
energy expenditures, the ratio of household energy expenditures to total household expenditures, and
the ratio of household energy expenditures to after-tax income across income quintiles and racial groups.
It is important to note that energy burden is sensitive to what energy services and expenditures are
included and how income is defined (e.g., whether transfer payments or taxes are included in income
calculation).
Table 33. Energy Expenditures by Quintiles of Income before Taxes, 2019
All
Lowest
20%
Second
20%
Third
20%
Fourth
20%
Highest
20%
Average income after taxes
$71,487
$12,236
$32,945
$53,123
$83,864
$174,777
Average annual expenditures
$63,036
$28,672
$40,472
$53,045
$71,173
$121,571
Natural gas
$416
$259
$355
$367
$455
$644
Electricity
$1,472
$1,049
$1,351
$1,446
$1,587
$1,924
Fuel oil and otherfuels
$113
$69
$101
$86
$121
$189
Gasoline, otherfuels, and motor oil
(transportation)
$2,094
$998
$1,601
$2,079
$2,593
$3,193
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Section 10—Distributional Analysis of Benefits and Costs of the Proposed Rule
Table 33. Energy Expenditures by Quintiles of Income before Taxes, 2019
All
Lowest
20%
Second
20%
Third
20%
Fourth
20%
Highest
20%
Total expenditures on energy
$4,095
$2,375
$3,408
$3,978
$4,756
$5,950
Energy expenditures as share of total
expenditures
6.5%
8.3%
8.4%
7.5%
6.7%
4.9%
Energy expenditures as share of income
5.7%
19.4%
10.3%
7.5%
5.7%
3.4%
Quintile's share of all energy expenditures
11.6%
16.7%
19.4%
23.2%
29.1%
Source: U.S. Bureau of Labor Statistics, 2020
Note: Income includes wages, self-employment income, Social Security and retirement payments, interest, dividends, rental
income and other property income, public assistance, unemployment and workers' compensation, veterans' benefits, and
regular contributions for support.
The data in Table 33 indicate that the highest income group consumes the most energy and spends the
most per household, but energy expenditures represent a smaller percentage of their total expenditures
and a smaller percentage of their income than the lowest income quintile. The lowest income quintile
accounted for 11.6 percent of energy expenditures, while the highest quintile accounted for 29 percent.
However, energy expenditures as a share of total household expenditures were 8.3 percent for the
lowest income quintile and 4.9 percent for the highest income quintile. For energy expenditures as a
share of average after-tax income, the distribution is more unequal, ranging from 19.4 percent for the
lowest income quintile to 3.4 percent for the highest income quintile. This means the lowest income
households are spending over five times more of their income on energy than the highest income
households. The highest income quintile spent about $6,000 per household on energy and had an
average after-tax income of $175,000 in 2019 while the lowest income quintile spent about $2,400 per
household on energy and had $12,000 of after-tax income. Thus, lower income households consume less
energy than high income households, but their energy expenditures account for a higher share of total
household expenditures on average and a higher share of after-tax income compared to higher income
households.
See Table 34 for average demographics by income quintile. Households in the lowest income quintile are
more than twice as likely to be Black than households in the highest income quintile. The higher income
groups also tend to be less likely to be Hispanic than the lower income groups.
Table 34. Demographics by Quintiles of Income before Taxes, 2019
Lowest
20%
Second
20%
Third
20%
Fourth
20%
Highest
20%
Number of consumer units
(thousands)
132,242
26,367
26,387
26,578
26,375
26,536
Black
13%
20%
16%
13%
10%
8%
White, Asian, and all other
races
87%
80%
84%
87%
90%
92%
Hispanic or Latino
14%
13%
17%
17%
12%
9%
Not Hispanic or Latino
86%
87%
83%
83%
88%
91%
Source: U.S. Bureau of Labor Statistics, 2020
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Section 10—Distributional Analysis of Benefits and Costs of the Proposed Rule
Table 35 and Table 36 show household energy expenditures by race and ethnicity. Black households'
energy expenditures represent a higher share of their total expenditures than for households of other
races, although their energy expenditures are lower. Hispanic households' energy expenditures comprise
a larger share of their total expenditures than non-Hispanic households, although they spend slightly
more per household on energy than non-Hispanic households. For Black households, energy expenditures
were about $3,700 in 2019 and accounted for about 8 percent of total expenditures and 7 percent of
after-tax income. For White and other non-Black households, energy expenditures accounted for about
6.4 percent of total expenditures and 5.7 percent of after-tax income, though they spent more on energy
($4,200 per household). For Hispanic households, energy expenditures were about $4,200 in 2019 and
accounted for about 8 percent of total expenditures and 7 percent of after-tax income. These numbers
are higher than for non-Hispanic households, whose energy expenditures accounted for about 6.3
percent of total expenditures and 5.6 percent of after-tax income, although non-Hispanic households
spent less on energy per household at $4,100.
Table 35. Energy Expenditures by Race, 2019
All
Consumer
Units
White,
Asian, and
All other
Races
White
and
All other
Races
(not
Asian)
Asian
Black
Number of consumer units (thousands)
132,242
114,554
108,246
6,308
17,688
Income before taxes
$82,852
$86,743
$85,417
$109,492
$57,649
Income after taxes
$71,487
$74,436
$73,341
$93,221
$52,389
Average annual expenditures
$63,036
$65,446
$64,981
$73,433
$47,230
Natural gas
$416
$417
$413
$481
$409
Electricity
$1,472
$1,479
$1,496
$1,192
$1,424
Fuel oil and otherfuels
$113
$123
$127
$42
$52
Gasoline, otherfuels, and motor oil
(transportation)
$2,094
$2,141
$2,146
$2,042
$1,794
Energy expenditures
$4,095
$4,160
$4,182
$3,757
$3,679
Energy expenditures as share of total
expenditures
6.5%
6.4%
6.4%
5.1%
7.8%
Energy expenditures as share of income
5.7%
5.6%
5.7%
4.0%
7.0%
Group's share of energy expenditures
100%
88%
84%
4%
12%
Source: U.S. Bureau of Labor Statistics, 2020
Note: Income includes wages, self-employment income, Social Security and retirement payments, interest, dividends, rental
income and other property income, public assistance, unemployment and workers' compensation, veterans' benefits, and
regular contributions for support.
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Section 10—Distributional Analysis of Benefits and Costs of the Proposed Rule
Table 36. Energy Expenditures by Race or Ethnicity, 2019
Non-
Non-
Hispanic
Black
All Consumer
Units
Hispanic
Non-
Hispanic
Hispanic
White,
other Races
Number of consumer units (thousands)
132,242
17,921
114,321
96,992
17,328
Income before taxes
$82,852
$64,577
$85,717
$90,734
$57,632
Income after taxes
$71,487
$60,235
$73,251
$76,983
$52,366
Average annual expenditures
$63,036
$54,734
$64,350
$67,370
$47,213
Natural gas
$416
$371
$423
$426
$407
Electricity
$1,472
$1,433
$1,478
$1,487
$1,426
Fuel oil and otherfuels
$113
$31
$126
$139
$51
Gasoline, otherfuels, and motor oil
(transportation)
$2,094
$2,438
$2,040
$2,083
$1,798
Energy expenditures
$4,095
$4,273
$4,067
$4,135
$3,682
Energy expenditures as share of total
expenditures
6.5%
7.8%
6.3%
6.1%
7.8%
Energy expenditures as share of income
5.7%
7.1%
5.6%
5.4%
7.0%
Group's share of energy expenditures
100%
14%
86%
74%
12%
Source: U.S. Bureau of Labor Statistics, 2020
Note: Income includes wages, self-employment income, Social Security and retirement payments, interest, dividends, rental
income and other property income, public assistance, unemployment and workers' compensation, veterans' benefits, and
regular contributions for support.
The CES data summarized in this section highlight the higher energy burdens experienced by low-income,
Black, and Hispanic households under baseline conditions. The proposed rule may increase energy prices,
which could exacerbate existing inequalities in energy burden.
EPA assessed the potential electricity price impacts of the proposed ELG on household electricity costs
assuming, as a worst-case scenario, that utilities may pass on all compliance costs to ratepayers. This
analysis, which is detailed in Chapter 7 of the 2023 RIA, suggested very small potential changes in
electricity costs as a result of the proposed rule. At the national level, average compliance costs per
residential households for Option 3 are $0.63 per year. These costs vary across North American Electric
Reliability Corporation (NERC)48 regions (see Figure 8), however, with average compliance costs per
residential households ranging from $0.09 per year in Western Electricity Coordinating Council (WECC) to
$1.31 per year in Reliability First Corporation (RF). As described above, lower-income households spend
less, in the absolute, on energy than do higher-income households, but energy expenditures represent a
larger share of their income. Therefore, electricity price increases tend to have a relatively larger effect
on lower-income households, compared to higher-income households. While the incremental burden
NERC regions include Midwest Reliability Organization (MRO), Northeast Power Coordinating Council (NPCC),
Reliability First Corporation (RF), SERC Reliability Corporation (SERC), Western Electricity Coordinating Council
(WECC), Texas Reliability Entity (TRE), Alaska Systems Coordinating Council (ASCC), and Hawaii Coordinating
Council (HICC). Compliance costs are zero in both the ASCC and HICC regions.
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Section 10—Distributional Analysis of Benefits and Costs of the Proposed Rule
relative to income is not distributionaIly neutral, i.e., any increase would affect lower-income households
to a greater extent than higher-income households, the proposed rule is expected to have a very small
impact in the absolute across all regions analyzed which is also small relatively as the potential price
increase is less than 0.1 percent of energy expenditures for all income and race groups, and even below
0.1 percent of just electricity expenditures for all but the bottom quintile income group in the most
impacted NERC region. Furthermore, these small impacts may be further moderated by existing pricing
structures.
126
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Section 10—Distributional Analysis of Benefits and Costs of the Proposed Rule
Figure 8. Estimated Average Annual Compliance Costs of the Proposed Rule (Option 3) per Residential Household, by NERC Region
127
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11. Limitations and Uncertainties
Table 37-43 present a discussion of the limitations and uncertainties of EPA's distributional analysis and
their potential effects on the analysis.
Table 37. Limitations and Uncertainties of EPA's Proximity and Community Screening Analyses
Uncertainty/Limitation
Effect on
Analysis
Notes
EPA used independent one-mile and three-mile
buffers around steam electric plant locations to
identify potentially affected populations.
Uncertain
Different portions of the same CBG may fall
within the buffer area of multiple steam
electric plants. As a result, some individuals
may be double counted when generating
associated statistics. This limitation only
affects around 2 percent of CBGs that fall
within the buffer areas.
EPA used the zip codes, and accordingly, ZCTAs
served by PWS, as reported in the SDWIS
database, as representative of the population
potentially affected by reductions in
halogenated disinfection by-products due to
steam electric power plant discharges.
Uncertain
ZCTAs and tribal areas can be served by
multiple PWS and some PWS serve people
across multiple ZCTAs, such that the affected
population may have different socioeconomic
characteristics.
Additionally, ZCTAs are approximate area
representations of USPS zip codes, so there is
some error present in the populations
included under respective zip codes.
Additionally, the U.S. Census Bureau is not
able to estimate ZCTAs for all USPS zip codes,
therefore, for EPA's analysis some systems
were not able to be analyzed as there were no
ZCTAs boundaries estimated for the zip
code(s) they served.
EPA used the SDWIS database and a zip code to
ZCTA crosswalk to identify ZCTAs served by
affected PWS. For any PWSIDs without any
associated ZCTA information, EPA used the PWS
Name and the PWS latitude and longitude to
identify associated tribal areas.
Uncertain
There may be some PWS that serve ZCTAs and
tribal areas. However, if only the ZCTA was
listed in SDWIS, the EJ analysis does not
account for the associated tribal area.
For systems EPA identified that were not found
in the UCMR4 dataset, the zip code reported for
the system in the SDWIS dataset was used as the
zip code served for that system.
Uncertain
The zip codes reported in the SDWIS dataset
represent the zip codes associated with the
location of the system, which may not in all
cases accurately represent the zip code(s)
served by the system.
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Section 11—Limitations and Uncertainties
Table 38. Limitations and Uncertainties of EPA's Distributional Analysis of Air Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
EPA used population projections from the Woods
and Poole dataset to analyze the distribution of
PM2.5 and ozone exposures among various
population groups.
Uncertain
There is uncertainty in the population projections
generated in the Woods and Poole (2015)
dataset.
The Woods and Poole database contains county-
level projections of population by age, sex, and
race out to 2050, relative to a baseline using the
2010 Census data. Population projections for
each county are determined simultaneously with
every other county in the U.S to consider
patterns of economic growth and migration.
Underlying the population projections are
forecasted variables such as income,
employment, and population. Each of these
forecasts require many assumptions: economy-
wide modeling to project income and
employment, net migration rates based on
employment opportunities and taking into
account fertility and mortality, and the
estimation of age/sex/race distributions at the
county-level based on historical rates of
mortality, fertility, and migration. To the extent
these patterns and assumptions have changed
since the population projections were estimated,
and to the extent that these patterns and
assumptions may change in the future, we would
expect the projections of future population
would be different than those used in this
analysis.
The baseline does not account for several
pending regulatory actions and newly enacted
statutory provisions.
Uncertain
The pending regulatory actions not included in
the baseline include regulatory actions that EPA
is proposing for the near terms and impacts of
the Inflation Reduction Act.
EPA used two air pollutant metrics, MDA8 (ppb)
and average annual PM2.5 concentrations (|ig/m3)
which are used to evaluate longer-term
exposures that have been linked to adverse
health effects.
Uncertain
The analysis does not evaluate distributional
disparities in other potentially health-relevant
metrics like shorter-term exposures to ozone and
PM2.5.
EPA's analysis was limited to assessing
distributional disparities in PIVb.sand ozone
exposures
Uncertain
The analysis did not extend to assess
distributional disparities in health effects from
PM2.5 and ozone exposures given the relatively
small changes in PIVh.sand ozone concentrations
resulting from Option 3 and additional
uncertainties associated with estimating health
effects stratified by population group and valuing
those effects.
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Section 11—Limitations and Uncertainties
Table 39. Limitations and Uncertainties of EPA's Distributional Analysis of
Immediate Receiving Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
IRW modeling is based on annual-average
pollutant loadings from the evaluated
wastestreams at steam electric power
plants and annual-average flow rates
within the immediate receiving waters and
does not consider temporal variability or
potential for pollutants to accumulate in
the environment over extended discharge
periods covering multiple years.
Underestimate
Uncertain effect regarding water quality
distributional analysis.
Likely underestimated effects for impacts to
wildlife and human health impacts due to long-
term accumulation.
Pollutant loading estimates are based on
average pollutant concentrations, not site-
specific data.
Uncertain
Likely results in overestimate of benchmark
exceedances for some immediate receiving
waters and underestimate of benchmark
exceedances at other immediate receiving
waters.
Modeling does not take into consideration
pollutant speciation within the receiving
stream.
Overestimate
This limitation is particularly relevant to the
wildlife impact analysis, as many of the ecological
impacts are tied to a specific pollutant species.
For example, inorganic arsenic is typically more
toxic to aquatic life than organic arsenic. This
limitation results in a potential overestimation of
the number of immediate receiving waters with
exceedances of water quality benchmark values
for inorganic forms of the pollutant (e.g., the
human health NRWQC for arsenic).
National-scale modeling assumptions that:
Do not include site-specific details or
detailed modeling of pollutants within the
receiving water.
Are used to estimate pollutant
concentrations in the fish tissue and to
evaluate wildlife impacts.
Are used to estimate human exposure
impacts.
Uncertain
1. See Appendix C of the 2020 EA for details. An
example of this can be found in Appendix D,
Exhibit E which details input provided by
community members in Florida regarding reverse
tidal flows contributing to pollutant loadings from
the local steam electric power plant
contaminating a local river.
2. See Appendix D of the 2023 EA for details.
3. Individual exposure factors, such as ingestion
rate, body weight, and exposure duration, are
variable due to physical characteristics, activities,
and behavior of the individual.
Does not take into account ambient
background pollutant concentrations or
contributions from other point and
nonpoint sources and other wastestreams
that may be discharged from the steam
electric power plant.
Underestimate
EPA's pollutant loadings analysis and IRW Model
runs specifically evaluate the changes in pollutant
loadings that result from the regulatory options
considered under the proposed supplemental
rule. Pollutant loadings from other wastestreams
at steam electric power plants are assumed to
remain the same under baseline and option
scenarios and are therefore not considered in the
analysis. Because of this approach, the modeling
likely underestimates the number and magnitude
of benchmark value exceedances at baseline and
under the regulatory options, which contributes
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Section 11—Limitations and Uncertainties
Table 39. Limitations and Uncertainties of EPA's Distributional Analysis of
Immediate Receiving Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
to uncertainty in the number of environmental
and human health improvements or impacts
under the proposed rule and evaluated regulatory
options relative to baseline.
Does not consider cumulative risks across
exposure pathways for ecological
receptors and subsistence and recreational
fishers.
Underestimate
Because many of the pollutants considered in this
analysis are bioaccumulative in nature, the model
considers only ingestion of the food source (fish),
because it is likely that the dose from the food
source is far greater than the dose from water
ingestion or direct contact with receiving waters.
The diet of the ecological receptors
consists entirely of fish inhabiting the
immediate receiving water and that all fish
consumed by subsistence and recreational
fishers (excluding two weeks per year) are
caught in the immediate receiving water.
Overestimate
This assumption potentially overestimates the
annual-average daily dose of the pollutants,
particularly for recreational fishers. The
proportion of fish eaten by an individual from
local surface waters will vary (e.g., consumption
rate estimates in studies might include seafood
purchased from a grocery store and not locally
caught).
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Section 11—Limitations and Uncertainties
Table 40. Limitations and Uncertainties of EPA's Distributional Analysis of
Downstream Surface Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
The IEUBK model does not capture very small
changes.
Negligible
The human health effects from reductions in
lead exposure analysis is based on the
Integrated Exposure Uptake Biokinetic (IEUBK)
model geometric mean blood lead (PbB)
values for each cohort in each CBG under the
baseline and the regulatory options. The IEUBK
model processes daily intake to two decimal
places (|ig/day), so some of the change
between the baseline and regulatory options is
not accounted for by using the model (i.e.,
IEUBK does not capture very small changes)
since the estimated reductions in adverse
health effects are driven by very small changes
across large populations. This aspect of the
model contributes to potential
underestimation of the lead-related health
effects in children in the different subgroups.
EPA estimated that all fishers travel up to 50
miles.
Uncertain
Certain subpopulations (e.g., low-income and
subsistence fishers) may tend to fish closer to
home. To the extent that these people fish
predominantly from waters receiving
discharges from steam electric power plants,
they may be exposed to relatively higher
concentrations of pollutants. Conversely,
people who live farther from steam electric
power plants may predominantly fish from
waters not affected by pollutants in steam
electric power plant discharges and be
exposed to relatively lower concentrations of
pollutants.
As data are not available on the share of the
fishing population that practices subsistence
fishing, EPA assumed that, uniformly across
the population (i.e., no distinction between
race and ethnicity, income, or other factors),
five percent of people who fish practice
subsistence fishing. This is based on the
assumed 95th percentile fish consumption
rate for this population in EPA's Exposure
Factors Handbook (U.S. EPA, 2011).
Underestimate
Subsistence fishers may represent a relatively
larger share of subpopulations of interest for
PEJC. This could increase inequities in the
baseline and affect the extent to which the
regulatory options may increase or decrease
these inequities.
EPA applied uniform fishing participation rates
and catch and release practices across the
entire population.
Uncertain
Differences in behavior across socioeconomic
groups may result in a different distribution of
baseline and regulatory option impacts.
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Section 11—Limitations and Uncertainties
Table 41. Limitations and Uncertainties of EPA's Distributional Analysis of Drinking Water Impacts
Uncertainty/Limitation
EPA's analysis of the distribution of drinking
water impacts evaluates the changes in TTHM
concentrations, bladder cancer cases, and
excess bladder cancer deaths across drinking
water systems under each of the regulatory
options.
Effect on
Analysis
Uncertain
Notes
EPA's analysis does not quantify the
distribution of TTHM concentrations, bladder
cancer cases, and excess bladder cancer
deaths across drinking water systems under
the baseline. Given this, EPA could not
conclude whether the changes modeled under
the regulatory options affected potential
distributional disparities-such as poorer
communities being less able to afford
treatment system upgrades to mitigate TTHM
formation leading to higher levels of TTHM
concentrations and incidence of bladder
cancer cases and deaths-among populations
served by affected drinking water systems
under the baseline.
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Section 11—Limitations and Uncertainties
Table 42. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks
Uncertainty/Limitation
Effect on
Analysis
Notes
EPA estimated the distribution of cumulative
risks across human health endpoints for only
mixtures of pollutants discharged to surface
waters from the evaluated wastestreams
included in the steam electric supplemental
rule.
Underestimate
The analysis did not extend to pollutant
loadings from other wastestreams present at
steam electric power plants or contributions
from other point or nonpoint sources. EPA's
pollutant loadings analysis and cumulative
impacts modeling runs specifically evaluate
the changes in pollutant loadings that result
from the regulatory options considered under
the proposed supplemental rule. Pollutant
loadings from other wastestreams at steam
electric power plants are assumed to remain
the same under baseline and option scenarios
and are not considered in the analysis.
Therefore, the pollutant loadings considered
in the analysis are an underestimate of the
total potential cumulative risk across human
health endpoints posed by steam electric
discharges to the environment.
Exposure concentrations for all pollutants
except lead in the cumulative risk analysis are
based only on steam electric power plant
discharges and do not reflect other potential
pollutant sources in the vicinity.
Underestimate
The cumulative risk analysis did not consider
pollutant loadings emitted from other sources
near the affected communities. Lead blood
concentrations used in the cumulative analysis
were the exception. The IEUBK model, used to
estimate lead blood concentrations,
considered lead contributions from soil, dust,
air, and water, in addition to lead
contributions from fish consumption from
waters that receive discharges of the
evaluated wastestreams. During public
meetings held by EPA with communities with
PEJC, participants often cited multiple sources
of pollution in their communities in addition
to the local plants that were of concern. This
suggests a potential underestimation of
distributional disparities in cumulative risks
among affected communities.
EPA limited the cumulative risks assessment
across human health endpoints for only
mixtures of pollutants with a published
Interaction Profile.
Underestimate
EPA identified only five pollutants (i.e.,
arsenic, cadmium, lead, methylmercury, and
zinc) in the IRW Model with published ATSDR
Interaction Profiles. EPA did not estimate
cumulative risks across human health
endpoints for mixtures of the remaining four
pollutants in the IRW Model. There may be
additional mixtures of concern that result in
cumulative impacts to communities not
represented in the analysis.
Results from the analysis are limited to the
distribution of cumulative risks across human
Underestimate
Lead is included in all three pollutant mixtures
evaluated in the cumulative risk analysis. The
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Section 11—Limitations and Uncertainties
Table 42. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks
Uncertainty/Limitation
Effect on
Analysis
Notes
health endpoints for only child cohorts under
the age of 11 years old.
IEUBK model only determines blood lead
concentrations for children under the age of
seven years old. Therefore, the cumulative risk
analysis for the methylmercury-lead and lead-
zinc mixtures are limited to child cohorts
under the age of 11 years old (based on
crosswalk of age groups). Arsenic-lead-
cadmium mixtures may also be limited to the
under 11 years old child cohorts if arsenic or
cadmium endpoint-specific HQvalues are not
greater than or equal to 0.1.
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Section 11—Limitations and Uncertainties
Table 43. Limitations and Uncertainties of EPA's Distributional Analysis of Costs and Benefits
Uncertainty/Limitation
Effect on Analysis
Notes
EPA's analysis of benefits focused on a subset
of benefits from the proposed regulation,
e.g., benefits from air pollution reductions
from steam electric power plants.
Underestimation
EPA's benefits analysis did not value
potential additional benefits resulting from
the proposed rule. For example, in EPA's
public meetings, community members
discussed predominantly using bottled
water for drinking water and everyday
household activities given their concerns
about pollutants in their drinking water from
steam electric power plants and emphasized
the high cost of doing so.
EPA's analysis of benefits from the proposed
rule evaluated benefits for the time period
2025-2049.
Underestimate
EPA's analysis did not calculate benefits to
affected populations from the proposed rule
after 2049, and therefore may not capture
longer-term effects on economic disparities
that may exist under the baseline. For
example, in EPA's public meetings,
community members noted long-term
economic losses in their communities due to
water pollution from steam electric power
plants damaging key industries like
recreational tourism. Improvements in
water quality in these communities as a
result of the proposed rule, therefore, may
have long-term benefits from reducing
averting behaviors and restoring livelihoods
in that may not be fully captured in the
benefits analysis.
EPA's analysis of the distribution of costs
focused on evaluating the distribution of the
changes in household electricity prices under
the proposed rule.
Underestimate
EPA's analysis of the distribution of costs did
not capture other costs with potential
disparities that may be incurred by affected
communities as a result of the proposed
rule.
EPA's distributional analysis of benefits and
costs qualitatively discusses potential
differences in apportionment of costs and
benefits among population groups of
concern.
Uncertain
EPA was not able to quantitatively analyze
the apportionment of costs and benefits
among population groups of concern given
the lack of information about how different
costs and benefits may be incurred across
population groups. For example, there is
uncertainty about how to value benefits
from air quality improvements across
various racial/ethnic groups.
136
-------
12. Conclusions
Overall, EPA's EJ analysis showed that the extent to which the technologies steam electric power plants
implement to control wastewater discharges will reduce differential baseline exposures for low-income
and minority populations in affected communities to pollutants in wastewater and resulting human
impacts varies. In particular, benefits associated with improvements to water quality, wildlife, and human
health resulting from reductions in pollutants in surface water and drinking water will accrue to minority
and low-income populations at a higher rate under some or all of the proposed regulatory options, with
Options 3 and 4 generating the greatest improvements. Remaining exposures, impacts, costs, and
benefits analyzed either accrue at a higher rate to populations which are not minority or low-income,
accrue proportionately to all populations, or are small enough that EPA could not conclude whether
changes in disproportionate impacts would occur. While the changes in GHGs attributable to the
proposed regulatory options are small compared to worldwide emissions, findings from peer-reviewed
evaluations demonstrate that actions that reduce GHG emissions are also likely to reduce climate-related
impacts on vulnerable communities, including low-income and minority communities.
137
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141
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Appendix A; Res-.iir -lom the Proxin mi >,i lysis of Downstream S' i rs
This section of the appendix presents the results of the nationwide proximity analysis EPA conducted to
assess the socioeconomic characteristics of communities living in proximity (within 50 miles) of a
downstream surface water receiving discharges from steam electric power plants. The socioeconomic
results presented are for Period 1 which covers the years 2025 through 2029 when the universe of plants
would transition from current (baseline) treatment practices to practices that achieve the revised effluent
limits.
-------
Appendix A: Results from the Proximity Analysis of Downstream Surface Waters
Table A-13. Percent of the Population Living within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected
Pollutants under the Regulatory Options Identifying as Low-Income Compared to the National Average (Period 1)
Pollutant
Changes in
Percentage of Reaches
Percent Low-Income
Concentrations
Option 1
Option 2
Option 3
Option 4
Option 1
Option 2
Option 3
Option 4
Antimony
Decreases
0.9%
32.8%
70.2%
75.1%
6.3%
15.6%
15.5%
15.7%
No changes
99.1%
67.2%
29.8%
24.9%
16.1%
15.5%
15.6%
15.4%
Arsenic
Decreases
66.2%
74.9%
89.7%
91.5%
15.4%
16.1%
15.9%
16.0%
No changes
33.8%
25.1%
10.3%
8.5%
15.9%
13.4%
13.6%
12.2%
Cadmium
Decreases
66.2%
74.9%
89.7%
91.5%
15.4%
16.1%
15.9%
16.0%
No changes
33.8%
25.1%
10.3%
8.5%
15.9%
13.4%
13.6%
12.2%
Cyanide(a)
Decreases
0.0%
70.0%
70.0%
91.2%
0.0%
16.9%
16.9%
18.8%
No changes
100.0%
30.0%
30.0%
8.8%
18.3%
23.0%
23.0%
7.9%
Lead(a)
Decreases
1.2%
41.5%
89.0%
95.1%
6.3%
15.5%
15.4%
15.6%
No changes
98.8%
58.5%
11.0%
4.9%
16.8%
16.7%
19.6%
20.1%
Manganese
Decreases
0.9%
32.8%
70.2%
75.1%
6.3%
15.6%
15.5%
15.7%
No changes
99.1%
67.2%
29.8%
24.9%
16.1%
15.5%
15.6%
15.4%
Mercury
Decreases
66.2%
74.9%
89.7%
91.5%
15.4%
16.1%
15.9%
16.0%
No changes
33.8%
25.1%
10.3%
8.5%
15.9%
13.4%
13.6%
12.2%
Thallium
Decreases
0.9%
32.8%
70.2%
75.1%
6.3%
15.6%
15.5%
15.7%
No changes
99.1%
67.2%
29.8%
24.9%
16.1%
15.5%
15.6%
15.4%
United States
13.7%
Source: U.S. EPA Analysis, 2023
Notes
a) Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for
those pollutants.
A-l
-------
Appendix A: Results from the Proximity Analysis of Downstream Surface Waters
Table A-2. Percent of the Population Living within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected
Pollutants under the Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 1)
Polluta
Changes in
Concentratio
ns
P
ercent of Reaches
Percent African American
Percent American
Indian/Alaska Native
Percent Asian
nt
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
n 1
n 2
n 3
n 4
n 1
n 2
n 3
n 4
n 1
n 2
n 3
n 4
n 1
n 2
n 3
n 4
Antimon
Decreases
0.9%
32.8%
70.2%
75.1%
0.1%
0.3%
0.6%
0.6%
6.8%
3.6%
3.3%
3.2%
0.0%
0.0%
0.1%
0.1%
y
No changes
99.1%
67.2%
29.8%
24.9%
0.5%
0.6%
0.3%
0.3%
3.5%
3.7%
4.2%
4.4%
0.1%
0.1%
0.1%
0.1%
Arsenic
Decreases
66.2%
74.9%
89.7%
91.5%
0.3%
0.3%
0.5%
0.5%
3.7%
3.8%
3.6%
3.6%
0.1%
0.1%
0.1%
0.1%
No changes
33.8%
25.1%
10.3%
8.5%
1.0%
1.2%
0.2%
0.2%
3.6%
3.3%
3.9%
4.1%
0.1%
0.1%
0.0%
0.0%
Cadmium
Decreases
66.2%
74.9%
89.7%
91.5%
0.3%
0.3%
0.5%
0.5%
3.7%
3.8%
3.6%
3.6%
0.1%
0.1%
0.1%
0.1%
No changes
33.8%
25.1%
10.3%
8.5%
1.0%
1.2%
0.2%
0.2%
3.6%
3.3%
3.9%
4.1%
0.1%
0.1%
0.0%
0.0%
Cyanide(
a)
Decreases
0.0%
70.0%
70.0%
91.2%
0.0%
0.3%
0.3%
0.3%
0.0%
3.2%
3.2%
3.1%
0.0%
0.0%
0.0%
0.0%
No changes
100.0
%
30.0%
30.0%
8.8%
0.3%
0.3%
0.3%
0.4%
3.0%
2.4%
2.4%
2.5%
0.0%
0.1%
0.1%
0.1%
Lead(a)
Decreases
1.2%
41.5%
89.0%
95.1%
0.1%
0.3%
0.6%
0.6%
6.8%
3.8%
3.5%
3.4%
0.0%
0.0%
0.1%
0.1%
No changes
98.8%
58.5%
11.0%
4.9%
0.6%
0.9%
0.2%
0.2%
3.5%
3.7%
5.9%
7.7%
0.1%
0.1%
0.1%
0.0%
Mangane
Decreases
0.9%
32.8%
70.2%
75.1%
0.1%
0.3%
0.6%
0.6%
6.8%
3.6%
3.3%
3.2%
0.0%
0.0%
0.1%
0.1%
se
No changes
99.1%
67.2%
29.8%
24.9%
0.5%
0.6%
0.3%
0.3%
3.5%
3.7%
4.2%
4.4%
0.1%
0.1%
0.1%
0.1%
Mercury
Decreases
66.2%
74.9%
89.7%
91.5%
0.3%
0.3%
0.5%
0.5%
3.7%
3.8%
3.6%
3.6%
0.1%
0.1%
0.1%
0.1%
No changes
33.8%
25.1%
10.3%
8.5%
1.0%
1.2%
0.2%
0.2%
3.6%
3.3%
3.9%
4.1%
0.1%
0.1%
0.0%
0.0%
Thallium
Decreases
0.9%
32.8%
70.2%
75.1%
0.1%
0.3%
0.6%
0.6%
6.8%
3.6%
3.3%
3.2%
0.0%
0.0%
0.1%
0.1%
No changes
99.1%
67.2%
29.8%
24.9%
0.5%
0.6%
0.3%
0.3%
3.5%
3.7%
4.2%
4.4%
0.1%
0.1%
0.1%
0.1%
| United States
| 12.2%
| 0.7%
I 5.4% |
Source: U.S. EPA Analysis, 2023
Notes:
a) Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for
those pollutants.
A-2
-------
Appendix A: Results from the Proximity Analysis of Downstream Surface Waters
Table A-3. Percent of the Population Living within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected
Pollutants under the Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 1)
Polluta
Changes in
Concentratio
ns
P
ercent of Reaches
Percent Native
Hawaiian/Pacific Islander
Percent Other non-Hispanic
Percent Hispanic/Lat
ino
nt
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
Optio
n 1
n 2
n 3
n 4
n 1
n 2
n 3
n 4
n 1
n 2
n 3
n 4
n 1
n 2
n 3
n 4
Antimon
Decreases
0.9%
32.8%
70.2%
75.1%
2.7%
2.3%
2.4%
2.4%
10.2%
12.4%
10.3%
10.1%
9.3%
13.7%
13.7%
13.7%
y
No changes
99.1%
67.2%
29.8%
24.9%
2.5%
2.6%
2.6%
2.6%
10.6%
9.5%
10.8%
11.2%
13.5%
13.1%
12.8%
12.7%
Arsenic
Decreases
66.2%
74.9%
89.7%
91.5%
2.5%
2.4%
2.5%
2.5%
9.6%
11.3%
11.1%
11.0%
13.1%
13.2%
13.4%
13.4%
No changes
33.8%
25.1%
10.3%
8.5%
2.5%
2.7%
2.3%
2.4%
12.8%
7.4%
7.2%
7.4%
13.9%
13.7%
13.0%
12.7%
Cadmium
Decreases
66.2%
74.9%
89.7%
91.5%
2.5%
2.4%
2.5%
2.5%
9.6%
11.3%
11.1%
11.0%
13.1%
13.2%
13.4%
13.4%
No changes
33.8%
25.1%
10.3%
8.5%
2.5%
2.7%
2.3%
2.4%
12.8%
7.4%
7.2%
7.4%
13.9%
13.7%
13.0%
12.7%
Cyanide
'(a)
Decreases
0.0%
70.0%
70.0%
91.2%
0.0%
2.2%
2.2%
2.2%
0.0%
13.1%
13.1%
12.0%
0.0%
14.5%
14.5%
14.6%
No changes
100.0
%
30.0%
30.0%
8.8%
2.2%
2.3%
2.3%
2.6%
11.8%
7.2%
7.2%
7.4%
14.5%
14.6%
14.6%
12.4%
Lead (a)
Decreases
1.2%
41.5%
89.0%
95.1%
2.7%
2.3%
2.4%
2.4%
10.2%
13.3%
11.0%
10.7%
9.3%
13.7%
13.7%
13.7%
No changes
98.8%
58.5%
11.0%
4.9%
2.5%
2.7%
3.0%
3.4%
11.0%
8.0%
10.5%
12.8%
13.5%
12.6%
10.4%
8.5%
Mangane
Decreases
0.9%
32.8%
70.2%
75.1%
2.7%
2.3%
2.4%
2.4%
10.2%
12.4%
10.3%
10.1%
9.3%
13.7%
13.7%
13.7%
se
No changes
99.1%
67.2%
29.8%
24.9%
2.5%
2.6%
2.6%
2.6%
10.6%
9.5%
10.8%
11.2%
13.5%
13.1%
12.8%
12.7%
Mercury
Decreases
66.2%
74.9%
89.7%
91.5%
2.5%
2.4%
2.5%
2.5%
9.6%
11.3%
11.1%
11.0%
13.1%
13.2%
13.4%
13.4%
No changes
33.8%
25.1%
10.3%
8.5%
2.5%
2.7%
2.3%
2.4%
12.8%
7.4%
7.2%
7.4%
13.9%
13.7%
13.0%
12.7%
Thallium
Decreases
0.9%
32.8%
70.2%
75.1%
2.7%
2.3%
2.4%
2.4%
10.2%
12.4%
10.3%
10.1%
9.3%
13.7%
13.7%
13.7%
No changes
99.1%
67.2%
29.8%
24.9%
2.5%
2.6%
2.6%
2.6%
10.6%
9.5%
10.8%
11.2%
13.5%
13.1%
12.8%
12.7%
| United States
| 0.2%
| 2.7%
| 18.8% |
Source: U.S. EPA Analysis, 2023
Notes:
a) Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for
those pollutants.
A-3
-------
Appenc Din the Screening Analyses
This section of the appendix presents the results of the screening analyses performed as part of EPA's
analysis of socioeconomic and environmental characteristics of communities expected to be affected by
the proposed rule. Correlation plots and box plots EPA generated through the EJSCREENBatch tool are
presented for each exposure pathway at the state and national levels, at each of the relevant radii. While
EPA developed an approach to identifying PEJC in communities using multiple indicator criteria
thresholds, the Agency notes that, as shown in the boxplots, the EJSCREENBatch tool uses a single
indicator criteria threshold, the 80th percentile, to assess PEJC in communities.
-------
Appendix B: Results from the Screening Analyses
Section 1: Results from the Air Screening Analysis
Figure B-l. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 1-mile Radius
&
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Age_Over_64 -0.26 -0.24 -0.3 -0.29 -0.29 (as
3.6
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B-l
-------
Appendix B: Results from the Screening Analyses
Figure B-2. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 1-mile Radius
Demographics relative to state
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Appendix B: Results from the Screening Analyses
Figure B-3. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 1-mile Radius
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Age_Over_64 -0.38 -0.27 -0.01 -0.51 -0.24 |) 3
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Risk_Mgmt_Plan_Facilities 0.29 0.11
Traffic_Proximity -0.01
B-3
-------
Appendix B: Results from the Screening Analyses
Figure B-4. National Percentile Socioeconomic and Environmental Indicators Box Plots using a 1-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-5. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 3-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-6. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 3-mile Radius
Demographics relative to state
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Appendix B: Results from the Screening Analyses
Figure B-7. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 3-mile Radius
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Air_Toxics_Cancer_Risk 0.45 -0.03 .0.05 -0.18 o 0.01 -0.16 0.17 -0.04 -0.03 -0.01
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Major_WW_Dischargers -0.01 -0.2 0 -0.03 0.12 0.08
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PM 0,21 -0.09 -0.04
Risk_Mgmt_Plan_Facilities 0.29 0.11
Traffic_Proximity 0.07
B-7
-------
Appendix B: Results from the Screening Analyses
Figure B-8. National Percentile Socioeconomic and Environmental Indicator Box Plots using a 3-mile Radius
Demographics relative to US
GIS Method: robust
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EJ Indexes relative to US
GIS Method: robust
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Appendix B: Results from the Screening Analyses
Section 2: Results from the Downstream Surface Water Screening Analysis
Figure B-9. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 1-mile Radius
Age_Over_64 -0.31 -0.2 -0.27 -0.34 -0.29
Age_Under_5 o -0.02 0.08 0.08
Less_than_HS_Edu 0.03 0.33 0.22
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0.22
0.57
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0.16
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0.31
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B-9
-------
Appendix B: Results from the Screening Analyses
Figure B-10. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 1-mile Radius
Demographics relative to state
GIS Method: fast
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EJ Indexes relative to state
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B-10
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Appendix B: Results from the Screening Analyses
Figure B-l 1. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 1-mile Radius
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Air_T oxics_Cancer_Risk
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B-ll
-------
Appendix B: Results from the Screening Analyses
Figure B-12. National Percentile Socioeconomic and Environmental Indicator Box Plots using a 1-mile Radius
Demographics relative to US
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Buffer: 1 mile Distance
EJ Indexes relative to US
GIS Method: fast
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Appendix B: Results from the Screening Analyses
Figure B-13. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 3-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-14. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 3-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-15. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 3-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-16. National Percentile Socioeconomic and Environmental Indicator Box Plots using a 3-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-17. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 50-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-18. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 50-mile Radius
Demographics relative to state
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Appendix B: Results from the Screening Analyses
Figure B-19. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 50-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-20. National Percentile Socioeconomic and Environmental Indicator Box Plots using a 50-mile Radius
Demographics relative to US
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EJ Indexes relative to US
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Appendix B: Results from the Screening Analyses
Figure B-21. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 100-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-22. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 100-mile Radius
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Appendix B: Results from the Screening Analyses
Figure B-23. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 100-mile Radius
-------
Appendix B: Results from the Screening Analyses
Figure B-24. National Percentile Socioeconomic and Environmental Indicator Box Plots using a 100-mile Radius
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Appendix B: Results from the Screening Analyses
Section 3: Results from the Drinking Water Screening Analysis
Figure B-25. State Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 0.01-mile Radius
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-------
Appendix B: Results from the Screening Analyses
Figure B- 26. State Percentile Socioeconomic and Environmental Indicator Box Plots using a 0.01-mile Radius
Demographics relative to state
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EJ Indexes relative to state
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B-26
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Appendix B: Results from the Screening Analyses
Figure B-27. National Percentile Socioeconomic and Environmental Indicator Correlation Plots using a 0.01-mile Radius
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-------
Appendix B: Results from the Screening Analyses
Figure B-28. National Percentile Socioeconomic and Environmental Indicator Box Plots using a 0.01-mile Radius
Demographics relative to US
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Appendix C: Public Outreach and Meeting Materials
Appendix C: Put treach and Meeting Materials
This section of the appendix presents the materials that EPA developed for its initial public outreach and
meetings the Agency conducted and held with a subset of communities expected to be affected by the
proposed rule that were identified by the Agency as having PEJC.
-------
Appendix C: Public Outreach and Meeting Materials
SERA
United States
Environmental Protection
Agency
omce of water
April 2022
Join Listening Sessions to Shape the Steam Electric Rule
Tne U.S. Environmental Protection Agency (EPA) is a federal
government agency whose mission is to protect Human and
environmental health. EPA can do this tnrougn laws mat limit
pollution from industrial sources into the environment
Introduction
EPA's Effluent Limitations Guidelines (ELG) program sets
national laws (regulations) to limit pollution into surface
waters—like lakes. rivers, and streams—from industrial
sources (Figure 1).
Figure 1: Exompie s or Industrial sources
Regulated DyELGs
Why Your Community's Input Matters
EPA is conducting an environmental justice (EJ) analysis
to wok at the pollution exposure for potentially affected
communities. EPA would like to meet with community
memoers to talk about tne following topics:
1. Ideas and strategies for limiting pollution rrom powef
plants.
2. Concerns rrom community memoers related to power
plants or other sources of pollution: nearny rivers, lakes,
and streams', or their drinking water.
3. community neaith, social or economic concerns.
How your Input Will be Used by EPA
epa will consider community input as it develops the
requirements for power plants. EPA will complete
calculations (analysis) on pollution exposures and health
effects across potentially affected communities.
Meat & Poultry Processing
Oil & Gas Extractkm
EPA will post information for communities to its
Supplemental steam Electric Rule weOsrte (nttpsv/www
eDa.aov.'ea/202lsuDDlemental-steam-electric-ruiemakinal
ji
1 4 », J*
« v» j'l t
II •Sfi&S&iiAA
¦
including:
• how epa used the community input
• The findings of tne analysis
Electricity Generation Pesticide & Chemical
Manufacturing
in August 2021, EPA announced tnat it will De developing
limits on polluted water released by power plants using
coal (Figure 2). Power plants must clean any polluted water
Before it flows into neartjy lakes, livers, and streams,
figure 2: Diagram or Polluted Water created
Dy Coal-tired Power Plants
I
• Next steps in the regulation process.
• Opportunities for communities to continue engagement
witn epa
Contact Information
Questions and Comments are Welcome!
if you nave questions or comments on tne Supplemental
Steam Electric Rule, please contact
Richard Benware
Email: oenware.richaro3epa.gov
Phone: 202.566.1369
\
if you have questions or comments on tne EJ Analysis.
please contact
Julia Monsarrat
Email: monsarratjuliaaepagov
Phone: 202.566.2887
Figure C-l. Community Outreach Factsheet
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Appendix C: Public Outreach and Meeting Materials
Supplemental Steam Electric Rule:
Information for Communities
Figure C-2. Community Meeting Presentation
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Appendix C: Public Outreach and Meeting Materials
Zoom Meeting Housekeeping
Audio is available through your computer's mic and speakers or by
telephone.
Type questions into the Chat box in the bottom dashboard.
To raise your hand, click the "Reactions" icon, in your dashboard, then click
"Raise Hand."
Please feel free to ask questions throughout the presentation.
Please contact Zachary.Arrnand@era.com if you are having technical issues
with Zoom.
% " pi - S&2 - P -1 ~ (#' ~
Unmute Start Video Participants V Chat / Share Screen Record Live Transcript
Leave
C-3
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Appendix C: Public Outreach and Meeting Materials
Why are we here? (Introduction)
The U.S. Environmental Protection Agency (EPA)
is a federal government agency whose mission is
to protect human and environmental health.
EPA can do this through laws that limit pollution
from industrial sources into the environment.
This meeting is intended to discuss water
pollution, specifically from local power plants.
jy United States
Environmental Protection
\r U K % Agency
Office of Water
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Appendix C: Public Outreach and Meeting Materials
What is the Effluent Limitations Guidelines Program?
Effluent Limitations Guidelines
(ELG) sets national laws (regulations)
to limit pollution into surface waters-
like lakes, rivers, and streams-from
industrial sources.
Examples of industrial sources regulated by ELGs include:
Steam Electric ELG sets
standards for cleaning
polluted water from power
plants that use coal to
produce electricity.
Supplemental
Steam
Electric
Rule
Meat & Poultry Processing Oil & Gas Extraction
Electricity Generation Pesticide & Chemical
Manufacturing
United States ....
Environmental Protection OtllCe Ol Water
LhI m m Agency
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Appendix C: Public Outreach and Meeting Materials
What is the Supplemental Steam Electric Rule?
• In August 2021, the EPA announced that it will be
developing limits on polluted water released by coal-fired
power plants.
• Previously, EPA updated limits for coal-fired power plants in
2015 and 2020.
• Power plants must clean any polluted water before it flows
into nearby lakes, rivers, and streams.
• The EPA can require plants to treat polluted water before
they discharge it or prevent them from discharging the
water at all.
¦—r*/V United States f ...
Environmental Protection OtflCe OT VV3ter
U M % Agency
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Appendix C: Public Outreach and Meeting Materials
What are the types of polluted water?
The Supplemental Steam Electric Rule will update standards for different types of polluted water released by coal-
fired power plants:
Bottom ash transport
and purge water: polluted
water containing ash from
burning coal
Landfill leachate:
polluted water from ash
ponds and landfills
FGD wastewater:
polluted water from wet
air pollution treatment
River
(or POTW)
v>EPA
FGD: Flue gas desulfurization
United States
Environmental Protection
Agency
Landfill Leachate
Legacy wastewater:
polluted water created and
stored in ash ponds before
the Supplemental Steam
Electric Rule goes into effect
Office of Water
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Appendix C: Public Outreach and Meeting Materials
Why does your community's input matter?
EPA is conducting an environmental justice (EJ) analysis to look at the pollution exposure
for potentially affected communities. EPA would like to meet with community members to
talk about the following topics:
1. Ideas and strategies for limiting pollution from power plants.
2. Concerns from community members related to power plants or other sources of
pollution; nearby rivers, lakes, and streams; or their drinking water.
3. Community health, social or economic concerns.
^r^JY ^n'tecl States
Environmental Protection
^1 Agency
Office of Water
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Appendix C: Public Outreach and Meeting Materials
How will your input be used by EPA?
EPA will consider community input as it develops the requirements for power plants. EPA will
complete calculations (analysis) on pollution exposures and health effects across potentially
affected communities.
EPA will post information for communities to its Supplemental Steam Electric Rule website
(https://www.epa.gov/eg/2021-supplemental-steam-electric-rulemaking) including:
• How EPA used the community input.
• The findings of the analysis.
• Next steps in the regulation process.
• Opportunities for communities to continue engagement with EPA.
United States
Environmental Protection
Agency
Office of Water
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Appendix C: Public Outreach and Meeting Materials
Discussion
United States
Environmental Protection
^1 Agency
Office of Water
c-io
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Appendix C: Public Outreach and Meeting Materials
&EPA
United States
Environmental Protection
Agency
Office of Water
Questions and comments are welcome!
'
-
If you have questions or comments on the Supplemental Steam
Electric Rule, please contact:
Richard Benware
Email: benware.richard@epa.gov
Phone: 202.566.1369
If you have questions or comments on the EJ Analysis, please
contact:
«4 Julia Monsarrat
- Email: monsarrat.julia@epa.gov
Phone: 202.566.2887
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Appendix C: Public Outreach and Meeting Materials
Appendix
United States
Environmental Protection
Agency
Office of Water
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Appendix C: Public Outreach and Meeting Materials
EPA's Statutory Authority
• Under the authority of the Clean Water Act (CWA), EPA establishes regulations
that apply to categories of industrial wastewater dischargers.
• These regulations are known as ELGs.
• The CWA section 304(b) requires EPA to annually review and, if appropriate,
revise ELGs. Every other year, EPA publishes a plan for new and revised ELGs,
after public review and comment.
• The Steam Electric Power Generating sector is considered a regulated industry.
United States
Environmental Protection
tl M % Agency
Office of Water
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Appendix C: Public Outreach and Meeting Materials
Technology-Based Effluent Limitations
• Technology-based effluent limitations (TBELs) require a minimum level of
treatment of pollutants for point source dischargers based on available treatment
technologies.
• The discharger can use any available technology to meet the limits.
• The Supplemental Steam Electric Rule is based on TBELs.
• One example of a potential TBEL is chemical precipitation technology used to treat FGD
wastewater. This is a tank-based system designed primarily to remove suspended solids.
United States
Environmental Protection
kl Agency
Office of Water
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Appendix C: Public Outreach and Meeting Materials
Water Quality-Based Effluent Limitations
• In some cases, TBELs alone will not achieve the applicable water quality
standard.
• The CWA allows development of water quality-based effluent limitations
(WQBELs) to ensure that the water body can meet its water quality goals with
the proposed discharge.
• Permit writers develop WQBELs based on site-specific factors. They can also be
derived from Total Maximum Daily Loads (TMDLs).
United States
Environmental Protection
IbI B % Agency
Office of Water
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Appenc >lic Meeting Notes
This section of the appendix provides detailed summaries of the public meetings that EPA held with a
subset of communities expected to be affected by the proposed rule that were identified by the Agency
as having PEJC.
-------
Appendix D: Public Meeting Notes
Exhibit A. Navajo Nation Community Meeting in Support of the Proposed Supplemental
Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category
May 11, 2022
Format: Virtual
Presenters:
• Richard Benware: EPA Office of Water (OW)
• Julia Monsarrat: EPA OW ORISE Fellow
Comments Regarding the Effluent Limitations Guidelines and Standards (ELG)
Rulemaking
• There is overlap between ELGs for coal ash wastewater discharges (under the Clean
Water Act) and the coal ash landfill and impoundment rule under the Resource
Conservation and Recovery Act (RCRA). In addition to bottom ash transport water
regulated by the current ELGs, participants noted there is also legacy coal ash discharges
seeping out of existing impoundments into Chaco Creek.
o EPA OW is coordinating with EPA Office of Land and Emergency Management
(OLEM) regarding the Coal Combustion and Residuals (CCR) Rule and
representatives attending this meeting can communicate any relevant information
to colleagues in EPA's Office of Land and Emergency Management (OLEM).
• Community participants support stricter (and the most stringent) ELGs and faster
timeframes for compliance. In addition, remediation of contaminated sites should have
faster timelines.
• The Steam Electric ELGs should impose regulations that eliminate discharges and
regulate all pollutants in these discharges. The rule should protect groundwater and all
groundwaters that flow into surface waters.
• Community members would like to eliminate the discharge of bottom ash water.
• EPA needs to protect Navajo Nation's scarce water resources.
• There is a limit to tribal consultation and consent. The process of government-to-
government communication is not fully transparent or communicated to community
members who have encountered issues across the community.
Environmental, Human Health, and Other Community Concerns
• There are a number of environmental justice (EJ) issues in the Four Corners region that
pertain to air quality, water quality, and cultural/spiritual impacts.
o Community members expressed concern with disproportionate impacts of
pollution, especially water pollution and resources, noting that these issues have
not abated over the long history of industry on Navajo Nation lands,
o The San Juan River is a cultural and spiritual river for the Dine people. It is
considered a male river and a provider,
o The Navajo Nation lacks infrastructure, including running water and electricity.
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Appendix D: Public Meeting Notes
o The Navajo Nation is currently dealing with climate-change related issues
including drought and dust storms. Local power plants in the area were once the
biggest polluters in the U.S., and community members noted the cumulative
effects have led to the current climate crisis,
o Lack of dependable water negatively impacts farming. Many community
members are self-sufficient through gardening and farming. People travel 30 to 40
miles to get safe water for drinking or agriculture. Some people are being forced
to sell their animals due to economic impacts,
o There are very few hospitals on the reservation (eight), making it very difficult for
people to travel to health centers. Community members must travel a long way to
get necessities like oxygen and medication. It is also expensive to make that trip
now, given high gas prices,
o The current environmental and health problems in the Navajo Nation community
are due to short-term profits of coal-fired power plants and other oil and gas
industries. The jobs in the extractive industries are not worth it when health and
entire communities are sacrificed in the process.
• Long-time community members noted that prior to the FCPP operation, in the 1950s and
1960s, the area included fields of flowers across the desert and dependable rainfall and
snowfalls that provided the needed precipitation. Currently, the landscape is dry and
barren.
o Once power plants opened in the area, the community began to experience air
pollution and visible smog, especially prior to power plants making the effort to
control the release of air pollutants. Even after installing wet scrubbers and other
infrastructure, community members noted that plant operators would turn off the
pollution control apparatus at sundown, allowing smog to spew out overnight.
This created a haze of pollution across the horizon in the morning,
o Growing up on a farm, one community member remembered noticing how the
water changed - becoming murky and polluted. Families without running water
would use river water for drinking and irrigation and would boil water before
drinking or using for cooking or washing.
• The Navajo Nation draws agricultural water from the San Juan River, and they do not
know the extent to which the power plant is putting pollutants into the river.
• In addition, the use of water resources from coal-fired power plants are significant. About
50,000 acre-feet of water is removed from San Juan River to cool the FCPP and San Juan
Generating Station. Reallocation of water resources would help bring the community
back to the condition it was in before the power plants opened.
• Community members expressed particular concern regarding inadequate handling of coal
ash waste at the FCPP. Since 1963, FCPP has generated coal ash and discarded it in a
number of places, including abandoned mine pits in the Navajo Mine, located adjacent to
FCPP and undisclosed locations around the area.
o In a report1, prepared by Dr. Campbell, a geologist who visited the site, FCPP
generated and disposed of at least 89 million tons of CCR.
1 https://earthiustice.org/sites/default/files/files/NGS-Expert-Report-GMA-6052017.pdf
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Appendix D: Public Meeting Notes
o There is concern regarding hazardous chemicals, such as mercury, lead, and
arsenic, and other pollutants in coal ash on the ground may be getting into the
waterways.
• Pollution in the Four Corners area has persisted for a long time and become heavily
impacted by climate change, nudification of the landscape, and sediment transfer.
Community members noted ecological dead zones near the coal-fired power plants. The
legacy of pollution is immense and includes selenium and mercury contamination.
• In addition to damage to the natural environment, community members have concerns
regarding the health impacts and damage to their physical bodies from the power plant.
Extractive industries have led to chronic diseases associated with air pollution. The whole
lifecycle of the power plant includes hazardous materials, from cutting up the land
(creating dust) to exhaust from power plants into the air. One meeting participant has
worked in public health with the Navajo community and observed adverse health impacts
in the community, including:
o Children with respiratory and cardiac problems, including observable increases in
children with asthma,
o Cancer and respiratory problems (emphysema, COPD, asthma),
o Diseases seen in the community take years to develop.
Another meeting participant noted that a lot of community members have physical and
mental disabilities. People in the Navajo Nation have high rates of cancer, cardiovascular
disease, and obesity, and the environment is compounding those health issues.
Receiving Water Characterization
• FCPP is on the Navajo Nation, a few miles south of the San Juan River. Water is
withdrawn out of the San Juan River upstream of the power plant and piped to a
manmade lake called Morgan Lake. The water is recirculated there and used for cooling
in the power plant, and discharges from the FCPP are sent to Morgan Lake. Water is also
discharged from Morgan Lake into a small wash called No Name Wash, which flows to
the Chaco River, which flows into the San Juan River.
o Morgan Lake was created by damming an unnamed tributary (which they believe
is No Named Wash) that used to flow into the Chaco River and then the San Juan
River. EPA has not recognized that Morgan Lake is a Water of the United States,
allowing FCPP to continue discharging into it as a cooling pond. This is important
because if receiving waters are not characterized correctly, they will not be
regulated.
Ongoing Concerns and Issues - Clean Up, Oversight, and Transparency
• The former owner (Australian company) left their ownership because of toxicity issues.
ana Public Service (APS) took over the power plant, but they were ill-equipped to
deal with the legacy issues of FCPP and the Navajo Mine.
o Companies have said that the polluted Four Corners area will be cleaned up but
community members have not found that to be the case after 60 to 70 years of
pollution. There have been numerous industries — uranium mining, hard rock
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Appendix D: Public Meeting Notes
mining, and coal, oil, and gas industries - to list as examples of previous failures
to take responsibility for clean-up.
• The FCPP lease site is on Navajo Nation lands. The Navajo Mine is owned by the Navajo
Transitional Energy Company (NTEC). which is a Navajo tribal corporation. NTEC
owns seven percent of the FCPP, and they have tried to own an additional 13 percent.
Due to this investment, community members are concerned that NTEC will continue
operating the coal-fired power plant for as long as possible. There is a lack of
transparency at NTEC, including information about its operations and communication to
the Navajo people about the toxicity of the pollutants from the FCPP.
o The FCPP provided jobs with good pay for people in the community; however,
the health and livelihoods of the communities along the San Juan River have been
heavily impacted.
• Regarding the disposal of CCR from FCPP, community members felt that APS has done
a poor job of monitoring and handling potential contamination from the disposal. The
community is concerned about water plumes, especially near the Chaco Wash that flows
into the San Juan River. The local population uses the San Juan River for recreational and
agricultural purposes. In his report, Dr. Campbell made some recommendations for
cleaning up the waste.
o Community members noted that there are many coal ash pits that are not lined,
and community members are not aware of whether the plant, regulatory
community, or other entity is checking whether toxins are leaking into waterways.
There is very little safe water on Navajo land.
o One community member who worked at the FCPP recalled taking a truck filled
with fly ash and dumping it on angled land, where it would likely runoff into the
river when it rained.
• Community members voiced concerns regarding employee safety when performing coal
ash handling at the FCPP. Contractors who work on the site go through a basic
introduction to safety but the training did not really apply to work at the FCPP. Based on
personal experience, one community member noted that they were never taught about the
composition of the coal ash and the health issues associated with it. During the
contractor's time at FCPP:
o Contractors climbed scaffolding to reach the top of smokestacks without safety
harnesses and there were reports of gear and tools falling on employees.
o Operations included vacuuming coal ash with a hose. The personal protective
equipment (PPE) included a basic disposable face mask, gloves, and safety
glasses. The ash gets all over the worker and into eyes and mouth even with the
PPE in place.
o There were always tight deadlines at the plant and no lunchbreaks during first few
weeks on the job. The contractor complained to supervisors about the lack of
lunchtime and the working conditions.
• Community members noted that to date, there has not been a single site where extraction
of a natural resource on Navajo Nation has been remediated, reclaimed, or restored to its
state before extraction. The community feels the lingering effects of outside corporations
D-4
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Appendix D: Public Meeting Notes
or state entities who are extracting those resources, which include uranium, oil, helium,
and coal. There is a sad history of extraction that speaks to failure of the U.S. federal
government to fulfill its responsibility to ensure that the land remains livable with
unpolluted land and clean air and water.
o For example, the 1979 Church Rock Uranium Mine spill was the largest
radioactive waste spill in the U.S. It released 94 million gallons of acidic
radioactive waste into Puerco River, contaminating over 80 miles of their
waterways that had been used to provide water for livestock, crops and water well
replenishment. This is an example of why frontline communities should be
consulted because they have generations of land knowledge that has been passed
down.
¦ Water wells that had been historically used are now polluted from the
uranium mine spill. Local people cannot drink the water, but still use it to
bathe and shower.
• It is important for EPA to conduct meaningful outreach and education about air and water
quality and to communicate that information in the native language.
EPA Permitting
• EPA needs to stop offering leniency to extractive industries. It took about 20 years to get
a National Pollutant Discharge Elimination System (NPDES) permit addressing pollution
into the San Juan River. This has been an area of neglect with concerns for the cyclical
nature of air and water pollution.
o A permit was last renewed for FCPP in 2001. Permits are supposed to be renewed
every five years. The local community noticed that the permit was behind in 2010
and notified EPA that the permit had not been updated.
¦ The Navajo Nation had adopted water quality standards that apply to some
of the streams. Some of the ELGs were also stricter. The permits needed
to be renewed to reflect more stringent regulation.
o The Navajo Nation ended up suing EPA to get the permit updated; this is an
environmental justice issue because EPA did not do its job. This resulted in
multiple legal challenges; the Navajo Nation should not have to sue EPA
repeatedly to get legal permits. A summary of the timeline included:
¦ After initial suit, EPA agreed to a date to renew the permit in a settlement.
EPA issued a permit, but the community challenged the permit in front of
EPA's Environmental Appeals Board (EAB) because the permit was
defective. In response, EPA withdrew the permit, which added a couple
more years to the process of getting a renewed permit for FCPP.
¦ EPA issued a new permit but the community identified issues with it,
including one related to the Steam Electric ELG, and brought these issues
to EPA's EAB. The EAB upheld EPA's permit, and the community
appealed that decision to the 9th Circuit Court of Appeals. They just
entered into a settlement unrelated to the Steam Electric ELG Rule to
address their concerns.
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Appendix D: Public Meeting Notes
• In the past, EPA has used its discretion to the benefit of the polluter on numerous
occasions.
o The first example is the decision to not classify Morgan Lake as a Water of the
U.S. and not regulate its discharges. The lake receives water from the San Juan
River and discharges water back into the San Juan River. EPA has acknowledged
previously that Morgan Lake was created by damming a stream that had valuable
ecological resources.
o Previous Steam Electric ELG Rules were also in favor of the polluter. Community
meeting participants argued that bottom ash discharges should be eliminated as
soon as possible, but EPA allowed the polluter to continue discharging bottom ash
until the last possible day.
o There is an enormous coal ash lake next to the FCPP. For years, the power plant
discharged coal ash mixed with water into the lake as a surface impoundment,
which eventually leaked. The leaks surfaced near the Chaco Creek, which flows
into the San Juan River. This forced APS to collect the leaking water and pump it
back into the same surface impoundment. This has created what appears to be a
perpetual pump-back system. EPA needs to regulate those seepages but has not
done so in the permits,
o EPA should use its discretion to protect public health and the environment in the
future.
• The Four Corners area includes three EPA regions (6, 8, and 9) and these regional offices
need to coordinate.
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Appendix D: Public Meeting Notes
Exhibit B. Kentucky Community Outreach Meeting in Support of the Proposed Supplemental
Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating
Point Source Category
May 17, 2022
Format: Virtual
Presenters:
• Richard Benware: EPA Headquarters Office of Water (OW)
• Julia Monsarrat: EPA Headquarters OW ORISE Fellow
Gene dcs and Examples
Comments Regarding the Effluent Limitations Guidelines and Standards (ELG)
Rulemaking
• Community members asked about the timeline for sharing feedback with EPA.
o OW Response: EPA explained that the purpose of the current meeting is to hear
from the community about what they would like included in the supplemental
ELG rulemaking, ways to improve community understanding of the rule and to
engage in further dialogue, and concerns within the community. EPA is interested
in setting up subsequent meetings after proposal to explain the analyses they
performed and listen to the community's opinions on the proposed rule.
• Community members asked if EPA is primarily focused on the Trimble Power Plant for
the Steam Electric ELG.
o OW Response: EPA explained that they are interested in any coal-fired steam
electric power plants in the U.S. that discharge the regulated wastestreams.
• Community members were concerned about leachate, since the Trimble Power Plant is
located along the Ohio River, and asked whether EPA plans to require the Trimble Power
Plant to use a specific treatment system for all leachate discharges.
o OW Response: EPA explained that they will be soliciting comment on whether
plants should co-treat flue gas desulfurization (FGD) and leachate, as some plants
do this practice. EPA has identified locations where plants treat leachate (alone),
including with zero discharge treatment. Leachate will continue to be generated at
landfills regardless of how well a cap is designed and EPA is looking at treatment
of leachate beyond FGD discharge.
• Community members noted that in 2018, EPA proposed to operate wet bottom ash
systems and purge 10 percent of transport water by volume on a rolling monthly basis.
The community members considered this to be a loophole and hoped that EPA would
eliminate it.
• Community members requested that EPA consider zero discharge for all wastestreams.
Zero discharge might be the best available technology (BAT) for at least some of the
wastestreams at Trimble Power Plant and other facilities.
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Appendix D: Public Meeting Notes
• Community members asked whether evaporative systems could be used in the Trimble
Power Plant.
o OW Response: EPA noted that some coal-fired power plants in the U.S. and other
countries use thermal treatment for discharge.
• Community members said that even though it might be more expensive for companies to
remove pollutants from wastestreams, it is more costly for human life if they do not
remove them.
• Community members asked EPA to require the state to conduct testing. They have not
been able to find data from state testing and find it difficult to communicate their
concerns to the state.
Environmental. Human Health, and Other Community Concerns
• Community members expressed concerns about the pollutants from the Trimble Power
Plant. They indicated that they did not know what pollutants are being discharged and
whether those pollutants present health concerns to people swimming and fishing in the
Ohio River. The plant is located in a community with EJ concerns, including air and
water pollution from multiple sources. Participants wanted to know how the rule would
change pollution from the plant and in the Ohio River in general.
o OW Response: As part of this rule development, EPA is currently looking at
impacts from the Trimble Power Plant and other plants along the Ohio River.
EPA is analyzing factors including carcinogens in downstream drinking water,
fishing and swimming impacts, and threatened and endangered species.
Regarding changes in pollutant loadings from the plant and into the river,
previous rulemakings by EPA have set more stringent limitations on heavy
pollutants and nutrients. The new rule aims for even more reduction from bottom
ash and leachate for the same pollutants and carcinogens.
• Community members are concerned about water quality, despite a 2019 drinking water
study conducted by the state that did not show significant levels of pollutants.
Community members indicated that other states have established lower limits than the
lifetime advisories from EPA. They would like to see this addressed, since people are
exposed to multiple chemicals from multiple sources of pollution.
• There is a proposed gun range in the area that could affect water quality in the creek. One
of the community members is affiliated with an organization that is opposed to the
proposed gun range.
• Community members explained that years ago, they were involved with the Red Penn
Landfill (near the Oldham-Jefferson County line), a 151-acre Superfund site with buried
drums. The leachate from the landfill travels underground to Floyds Fort Creek and other
waters, eventually reaching the Ohio River. There are concerns about paint cans that
could contain lead or PFAS seeping from the landfill and entering these waters. The
federal government was involved in the Red Penn Landfill cleanup, and the landfill was
eventually turned over to the state, but it was not capped for many years. Community
members said that orange leachate comes out underground and runs into Floyds Fork
Creek (see Receiving Water Characterization section).
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Appendix D: Public Meeting Notes
o Floyds Fork Creek runs through the Parklands of Ftoyds Fork, which has walking
trails, kayaks, and canoes. The park is heavily used by the public and spans
several counties.
o Community members said that they do not know whether EPA has tested water
downstream of the landfill or whether there are requirements to test the water,
o The Floyds Fork Wastewater Treatment Plant is in the area, along with other
subregional treatment plants,
o One community member recently participated in a survey with a wildlife agency
and documented nearly 71,000 dead fish resulting from an upstream fire and a
deoxygenated plume that extended downstream.
• There are different types of outdoor recreation in the local waterways.
o There are many fish in Floyds Fork Creek, such as catfish, sunfish, and bass.
Many people fish and seine for crayfish,
o Community members enjoy fishing, kayaking, and canoeing on the Ohio River. In
general, there are many opportunities for outdoor recreation in Oldham County,
and many people use the waterways.
• Community members said that they thought that EPA must consult with the U. S. Fish and
Wildlife Service and prepare a biological opinion on the impacts from steam electric
power plant discharges.
• Community members expressed concerns about environmental quality in the west end of
Louisville.
o There are 11 large industrial plants in this area. Community members said that
residents in this region die 10 to 12 years earlier than residents living in the east
end of the city. Companies such as Dupont (now Chemours), Dow Dupont, and
Lubrizol used to be located in the west end of the city,
o The west end of Louisville has a higher proportion of Black residents relative to
the rest of the city. In this area, Rubbertown in Jefferson County has a lot of
underserved and overlooked residents. No one from that area participated in the
meeting, but community members indicated that there are likely many EJ issues
in that region.
o Community members said that there are heavy fumes in the west end and no
walking trails. Chickasaw Park is located in this part of the city,
o There is a high rate of illness and cancer in this area. Many Rubbertown residents
are low-income and cannot afford high-quality medical care,
o The region is also a food desert.
• In the east end of Louisville, there was a proposal to add walking trails near a landfill,
and community members fought it because of the fumes.
• There are rumors in some part of town that EPA has told residents to put tarps on the
ground before children play outside.
• Community members said that emissions from the Trimble Power Plant can be carried
for miles, and a lot will land on the ground and be washed into the aquifers. As a result,
they expect that many local waterways could be affected.
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Appendix D: Public Meeting Notes
• There are high rates of cancer in Louisville. In particular, community members know
many people who have had kidney cancer.
o There is a cancer center in Louisville that might have more information on local
cancer rates.
o There are notable rates of brain cancer in the community of Fern Creek. Cedar
Creek, a major tributary to Floyds Fork Creek, runs through this area.
• Community member asked whether EPA was considering the effect of water quality on
wildlife.
o OW Response: EPA confirmed that they review this topic as part of the Steam
Electric ELG.
• Community members asked whether EPA was considering PFAS and "forever
chemicals" as part of the Steam Electric ELG.
o OW Response: EPA explained that EPA has an Agency-wide PFAS action plan.
o Recent local news stories have reported high concentrations of PFAS in
Henderson, Kentucky, where Teflon pans were being recycled.
o The local water company currently tests for 16 to 17 PFAS. Community members
said that EPA will be requiring them to test for 29 PFAS.
Receiving Water Characterization
• Floyds Fork Creek flows into the Salt River, the Ohio River, and ultimately the
Mississippi River. It runs through five counties and includes many tributaries.
• Currys Fork is a large tributary to Floyds Fork Creek.
Ongoing Concerns and Issues - Clean Up, Oversight, and Transparency
• The public is generally not aware of potential pollutant exposure from Trimble Power
Plant.
o Community members receive marketing newsletters from Trimble Power Plant
with updates on news such as treatment technologies. They only hear the positive
aspects of the power plant from the utilities, and they do not know if the
information is accurate. However, they have doubts about the health risks from
the power plant. They are not aware of anyone taking water samples upstream and
downstream of the power plant, and they do not know if there is an issue in the
river.
o Community members said it would be helpful if Trimble Power Plant was
required to regularly post information to a website, especially if that information
was presented for a general audience.
• There is an interest in press releases from EPA. Oldham County has a newspaper that
would publish press releases written for the general public.
• It might be possible for EPA to submit a public service announcement to local radio
stations. Louisville Public Media has covered local PFAS issues.
• There is a substantial Spanish-speaking population in the Louisville area. For example,
many Hispanic employees work on horse farms in Oldham County. As a result,
community members recommended that EPA publish materials in Spanish.
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Appendix D: Public Meeting Notes
Exhibit C. North Carolina Community Meeting in Support of the Proposed Supplemental
Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category
June 23, 2022
Format: Hybrid
Presenters:
• Richard Benware: EPA Office of Water (OW)
• James Covington: EPA OW
• Julia Monsarrat: EPA OW ORISE Fellow
General Topics and Examples
• Belews Lake community is widely spread out over four counties, contributing to the lack
of understanding on environmental pollution and human health concerns.
• One community member remarked that the Clean Smoke Stacks Act was passed 20 years
ago that improved air quality but increased water pollution.
• Most community members express concern on the coal ash soil and water contamination
but have been told that the ash is "clean" by industry. A community member feels that
Duke Energy does not accurately communicate the potential hazards of the ash and other
pollution due to the potential liability.
• Many surrounding communities who would like to test their water do not have adequate
water sampling equipment.
• Community members requested that an independent contractor frequently collect soil and
water concentration data from Belews Creek and post the information on a publicly
available website as they distrust Duke Energy.
Comments Regarding the Effluent Limitations Guidelines and Standards (ELG)
Rulemaking
• Community members would prefer zero discharge at Belews Creek Steam Station since
the technology (i.e., membrane filtration) is available to achieve it, could be installed
quickly, and would treat bromide. They do not want NC DEQ to decide which
technology is best to implement.
• What is the timeline for proposing a rule and how will EPA use information from this
meeting?
o OW Response: EPA plans to publish revisions to the Steam Electric Rule in Fall
2022. EPA would like to hold one or more public hearings after the proposed rule,
and there will be a 90-day public comment period before issuing a final rule. EPA
would like to gather feedback from community members on health and
socioeconomic impacts from power plants, other industrial sources, and other
background concerns.
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Appendix D: Public Meeting Notes
Community Impacts Caused by the Power Plant
• A Black and low-income community established in the 1970s was negatively impacted
by the Belews Creek Steam Station, including coal ash disintegrating paint from houses
and contaminating groundwater. Banks stopped loaning money due to the contamination,
and many people left because the water and soil was contaminated. Overall, the
community does not feel that their concerns have been heard by industry representatives,
permitting authorities, or lawmakers.
• The community expressed concern that the elementary school closest to the power plant
is expected to close in response to the Dan River coal ash spill; they expressed that
schools are essential to neighborhoods. In addition to children, other vulnerable
populations in the community include rural, communities of color, elderly, and those that
have a harder time affording and accessing healthcare.
• Community members estimate that effluent from the power plant killed 90 percent of fish
species in Belews Lake (a cooling pond) which previously was a food source. Most locals
are aware of the pollution and no longer fish in the lake; however, there are tourists and
community members with language barriers that do still fish.
Economic Concerns
• There are three new businesses in Madison that are tied to the Dan River, including
tobacco farming, and community members expressed concern that inadequate power
plant wastewater treatment would impact those businesses.
• Other economic concerns include 70 percent of children receiving free and reduced
lunch, and most schools being designated as Title I (children from low-income families
comprise at least 40 percent of enrollment). Parents who have environmental pollution
concerns may not have time to come to a community outreach meeting as they are
working multiple jobs.
• As a result of the coal ash spill, there is a concern that the tourism industry will be
affected as more people move away. A community member noted there is a campground
located near the Dan River.
• Community members also expressed a desire for the pollution fines that Duke pays to go
towards benefitting community members. Home values are very low, and many
community members cannot afford to move.
• The nearby Miller-Coors Plant closed that previously employed 300 people. The plant
did not publicly give a reason for its closure, but community members suspect there were
source water quality issues as it was drawing from the Dan River.
Human Health Concerns
• A community member expressed concern on selenium and bromide concentrations in
Belews Lake, and overall concern on heavy metals in well water. There is a concern that
even though some pollutants are discharged in small concentrations, chronic exposure
can impact health.
• In the years following the coal ash spill, the municipalities of Eden and Madison had high
total trihalomethanes (TTHMs). Trihalomethanes (THMs) may form in the finished
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Appendix D: Public Meeting Notes
drinking water as the water moves through the distribution line due to elevated bromide
concentration. Some communities have resorted to venting water from fire hydrants to
avoid THMs; rural communities do not have the resources to do this.
• Specific impacts include needing to buy bottled water to bathe young children and to use
as drinking water.
• Many community members do not have health insurance. There are unusually high rates
of cancer, diabetes, skin disorders, and reproductive issues, as compared to other counties
in NC. Children especially have high rates of bronchitis and asthma.
Other Background Concerns
• Although community members may receive SNAP benefits, there are very few grocery
stores in the area, and the community is considered food impoverished by USDA criteria.
In addition, there is very little public transportation, and gas is expensive.
• Internet access is limited and is more likely to be available in households with school age
children.
• Poultry contamination is concerning, including E. coli discharge into streams from
uncovered litter piles. Due to national security concerns, these facilities have limited
permitting, and community members do not know where they are located. In addition,
industrial poultry facilities cause the closure of smaller, family-run operations.
• One community member also expressed concern on 1,4-dioxane discharges stemming
from agricultural applications (e.g., tobacco). NC DEQ is planning to establish a
discharge level of 0.2 parts per trillion (ppt); however, analytical instrumentation is only
able to reliably detect 1 ppt. This may cause businesses to relocate as it essentially
prevents them from using the chemical. EPA has not taken formal action on 1,4-dioxane,
even though studies have been on-going since the 1970s. The community member would
like EPA to establish the threshold instead of the state.
• Other industrial activity in the area includes logging, textiles, and furniture finishing, who
have not adequately addressed their environmental pollution. Furniture finishing is the
only major employer in Stokesville.
Additional Communication
• There is no printed newspaper in the community near Belews Lake, and community
members suggested mail-based outreach or a canvassing effort to notify residents of the
next community outreach meeting. They also suggested that municipalities be notified of
the next meeting, and in particular, those in the public health department. There are
digital newspapers, including Stokes News and Rockingham Now, that could also be
used for outreach.
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Appendix D: Public Meeting Notes
Exhibit D. Texas Community Meeting in Support of the Proposed Supplemental
Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating
Point Source Category
June 30, 2022
Format: In-Person/Virtual
Presenters:
• Richard Benware: EPA Office of Water (OW)
• James Covington: EPA OW
• Julia Monsarrat: EPA OW ORISE Fellow
Comments Regarding the Effluent Limitations Guidelines and Standards (ELG)
Rulemaking
• Supreme Court Ruling from June 30, 2022: The community is curious about how the
supreme court ruling that restricts EPA's authority to mandate carbon emissions
reductions will impact the Steam Electric ELG.
o OW Response: As this was a recent event, EPA will need to wait to respond
following review by attorneys to determine how or whether this ruling will impact
other EPA rules going forward. This ruling was specifically for greenhouse gas
emissions (GHG), which is covered under a different law than the ELGs. Under
the Clean Water Act (governs water rules), there are set factors that EPA needs to
consider, and this statute has been decided over the years.
• What is the timeline of the rulemaking, including assessing these comments and
proposing the rule?
o OW Response: EPA plans to sign the proposed rule in the fall, then there will be a
comment period. EPA analyzes the comments and makes changes to the analyses.
This process will likely take until 2024 for a final rule.
o Today is screening level meeting where EPA will hear what the community wants
to express. There are other opportunities for providing comments. EPA will post a
draft version of the supplemental rule to its website and officially publish in the
Federal Register Notice (FRN). Following publication, there is a formal comment
process where anyone can submit comments for the federal record and EPA
responds to those comments. Following proposal of the rule, EPA will hold public
hearings and is looking to hold in-person meetings at communities where there
are EJ concerns. EPA will consider input from today's meeting and any
comments submitted or provided at public hearings. EPA will consider comments
received during and after proposal of the rule when developing the final rule.
• What technologies are EPA considering for the supplemental rulemaking?
o OW Response: Under this statute, EPA evaluates the technology, along with a
review of pollutants. This knowledge of the treatment technologies drives
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Appendix D: Public Meeting Notes
decisions. EPA looks at costs for the technology, impacts from pollutants, and
improvements (pollutant reduction) by installing treatment technologies. EPA is
in the process of finalizing technology selection for the proposed rule and is
looking at potentially more stringent options like membrane filtration and spray
dryer evaporators that can remove heavy metals and other pollutants.
• Community members asked about public health impacts from the pollutants that EPA is
trying to regulate and what impacts would be to the community. In addition, asking how
EPA weighs public health vs. costs.
o OW Response: In general, ELGs are based on economic achievability and
availability factors. EPA cannot make/change decisions based on a cost-benefit
analysis, specifically prohibited by the CWA ELG program. In previous Steam
Electric ELG rules, EPA has addressed discharges of heavy metals and nutrients.
EPA conducts analysis to evaluate improvements in water quality and decreases
in concentrations of pollutants in fish. Current rule does not address halogen
(bromide, iodine) and dissolved metals. (See EPA website for more details on
pollutants and analysis performed for the 2020 rule:
https://www.epa.eov/ee/2020-steam-electric-reconsideration-rule).
Environmental. Human Health, and Other Community Concerns, Including Access to
Information
• The community is concerned about migration of pollutants from the Parish Plant via the
groundwater. Using Ashtracker.org, the participant looked at groundwater monitoring
wells for 16 active power plants, finding that almost all had pollutants above federal
limits. The participant specified that almost every well at the Parish Plant had pollutant
levels that exceeded federal standard levels.
• The community is also concerned about the impacts these exceedances may have on the
community. The community would like more information on how the water and soil is
being impacted due to the Parish Plant, how widespread the pollution is, and if EPA can
make that data available to the public so that they can stay informed and avoid highly
contaminated areas.
• The community would like to see EPA engage with the state and county public health
offices to keep the community informed if there are high cancer ratings. One attendee
noted a study from Rice that looked at health benefits of closed coal plants and identified
statistical deaths from all plants in Texas. The Parish Plant's particulate matter (air
emission) accounted for the greatest number of statistical deaths (178 every year) in
Texas.
o OW Response: The ELG program normally does not coordinate with state and
local health departments. Other parts of the Agency do engage in those types of
activities. If there is information about a plant that someone would like to be
brought up, EPA can pass along to the state.
• Meeting participants know that some lakes have been exposed to pollutants from plant
discharges (downstream). People go fishing and don't understand why they are getting
sick. Communities around plants are using this water on lawns and parks around homes.
How do we address this and get it cleaned up?
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Appendix D: Public Meeting Notes
o OW Response: Some of those issues are under the disposal rule (Coal
Combustion and Residuals (CCR) Rule) implemented by EPA's Office of Land
and Emergency Management (OLEM). There is a potential that plants close to
surface waters would fall under OW purview. For example, the Maui case ruling
found that if plant is right up against a surface water body, then you could have a
functional equivalent discharge that could be captured in ELG requirements.
Downstream cleanups of discharges happen under the EPA Superfund program.
With this rulemaking, EPA is looking at future discharges to help stop pollutants
getting into the environment,
o One of the wastestreams being evaluated is legacy wastewater. This wastewater is
still on plant property. Although the ELG does not address legacy pollution, it can
evaluate ways to not add more.
• The attendee indicated that the Parish Plant is a violator and has concerns of the effects of
ash. The community would like more information to answer questions such as: 1) What
are the parameters of the pollution around the plant and impacted mile radius/downstream
area? 2) How can we access the data to determine what we need to communicate with the
public?
o OW Response: As part of the ELG development, EPA conducts a downstream
analysis. Some of these contaminants do not break down and can travel dozens of
miles and make it downstream to water treatment plants. There is a point where it
gets diluted from other streams. That type of data will be in the rulemaking
record. EPA can help point out where the data are available. (See
https://www.epa.eov/ee/2020-steam-electric-reconsideration-rule-dociiments that
includes EPA's engineering, environmental assessment, and cost and benefits
analyses documents from the 2020 rulemaking and docket (record) user's guide.
Similar documents and docket materials will be available for the proposed
supplemental rule.)
• Scrubbers on FGD Systems: The community around the Parish Plant is aware that the
plant has flue gas desulfurization (FGD) systems, many of which do not have air
pollutant control scrubbers. One attendee mentioned that only one unit out of four is
equipped with a scrubber. The attendee wants to know what impact that has on the
pollutants in the wastewater.
o OW Response: Wet-systems (scrubbers) are sometimes needed to meet Clean Air
Act (CAA) regulations; however, plants may use dry air pollution control systems
and truck solids to a landfill. Under the CAA, a plant might be small and exempt
from requirements. The ELG covers wastewater from FGD (wet scrubber)
systems. Some plants are able to recycle and reuse this water, others use
evaporation ponds, and then there are ones that need to discharge (unable to
reuse). Under the CAA, if plants are grandfathered, the ELG will not impact
them. However, the ELG could have indirect impact, and the plant may choose to
close.
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Appendix D: Public Meeting Notes
Other Sources of Environmental Pollution in the Area
• The community is concerned with the sprawl in the area and how that creates air
pollution and ozone issues. One community member noted that they are in non-
attainment and have been since 1979. There is also concern about the oil wells along the
Fort Bend toll road from East Bend to Richmond. People are having problems with oil
well seepage.
• Another attendee mentioned the large portion of the population getting cancer possibly
due to the oil wells, nearby chemical plants, or leachate problems coming from the
landfill.
• Participants are concerned about new homes and schools being built near Winfield Lakes.
Currently there are odor problems, and the community would like information on
potential pollution sources in the area (e.g., leaks).
• Exposed land with leachate can be seen as well.
Community Needs for Monitoring, Oversight, and Guidance
• One of the noted environmental concerns described above is the potential for pollutants
to migrate via groundwater (e.g., from landfills and surface impoundments). Community
members asked about well monitoring in their area and whether EPA reviews the
groundwater monitoring results or manages the well monitoring. Community members
also do not trust that the Parish Plant has stopped intaking coal in their impoundment or
fully monitoring the groundwater as required by the CCR Rule.
o OW Response: EPA implements the CCR Rule through OLEM. The CCR Rule
has requirements to clean up existing coal ash storage and to conduct groundwater
monitoring from landfills and surface impoundments at downgradient locations.
Power plants perform the assessment to establish a baseline (needed to determine
migration) and outreach to remediate any groundwater contamination. EPA has
the power to initiate enforcement actions. The public can look up data for
facilities under the CCR part A and part B rule. Some plants have asked for
extensions to meet requirements, and others say that their storage is protected
("safe") even if unlined. EPA's website tracks EPA actions. For the supplemental
rule ELG, EPA is evaluating requirements for leachate discharges.
• As EPA has determined a new rulemaking is needed, what kind of guidance can be given
to people to make sure they are safe (e.g., children playing outside and people being
outdoors) until limits are being met?
o OW Response: As noted earlier, under the CWA, ELG limitations are based on
technology. It is the role of the state (Texas) department to looks at water quality
standards - are they being exceeded for a given waterbody and its uses or do they
need to issue a fish consumption advisory. When a discharge permit is written by
the state, they must look at both technology and water quality requirements and
apply the most stringent limit.
NPDES Permitting - Accountability and Transparency
• The community does not believe that the Texas DEQ cares about EJ and that they do not
take demographic information into consideration when writing permits. The community
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Appendix D: Public Meeting Notes
wants to know if EPA will review TDEQ permits and whether due process is completed,
and if EPA can give direct oversight to the state department.
o OW Response: Primacy is with the state agencies. EPA does have discussions
with states, as partners, to ensure regulations are being adhered to. There is some
state discretion. EPA does not plan on looking at state permitting authority
performance as part of this rulemaking. We have seen some states do more about
issues being reviewed for this rule (e.g., NC and dewatering of ponds). TDEQ is
participating in this meeting virtually to hear comments and concerns.
• The community would also like more transparency and would like to have more input
with Texas DEQ when creating permits. There was an overall sense of distrust and anger
towards the DEQ. Many community members agreed that they would like to see the
Texas DEQ disbanded. They believe EPA is too disconnected at the county and city
level. One way to improve trust is through transparency and being able to access data
publicly.
• Community members would like to see Texas DEQ take demographics (EJ concerns) and
cumulative impacts into account when writing permits.
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Appendix D: Public Meeting Notes
Exhibit E. Florida Community Meeting in Support of the Proposed Supplemental
Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category
September 7, 2022
Format: Virtual
Presenters:
• Richard Benware: EPA Office of Water (OW)
• Julia Monsarrat: EPA OW ORISE Fellow
Questions and discussions with the community members are summarized below.
Comments Regarding the Effluent Limitations Guidelines and Standards (ELG)
Rulemaking
• Do EPA's assessments only apply to the plants themselves, or is EPA also looking at
temporary storage facilities and/or auxiliary sites?
o OW Response: This analysis will not be a catch-all for all sources; EPA uses an
annual-basis analysis. Combustion residual leachate can come from landfills and
surface impoundments. EPA evaluates plant utilization and tends to look at large
pollutant sources, such as those identified in EPA's Toxic Release Inventory
(https://www.epa.eov/toxics-release4nventorY4ri-proeram). Those sources may
capture the temporary storage areas if they cross the reporting threshold. If you
are aware of storage areas outside of the primary sources that EPA identifies, we
would be interested in further information. For example, coal ash storage where
leaching may be occurring might be in the scope of the analysis.
• EPA's analysis considers both the financial/economic cost to regulations along with the
impact on health and long-term ramifications for environmental justice. How are these
factors weighted?
o OW Response: The Clean Water Act (CWA) includes a list of factors EPA
considers for ELGs. EPA can make regulations based on best available
technology economically achievable (BAT) across the industry. EPA asks, "Can
the industry bear the cost?" We also look at non-water quality environmental
impacts such as air emissions, soil impacts, and electricity generation. EPA has
some discretion in weighing those factors. This is done at the Administrator level.
The CWA prohibits EPA from using health impacts or cost/benefit weighting.
EPA determines BAT and considers cost for overall reasonableness. The cost to
the utility is not paramount. Even in other rules, cost is a factor but is used in
determining the overall achievability. There have been rules with very high costs
where EPA has found that something is not economically achievable or could
impact a particular location. In those cases, the economic factors can take a front
seat (e.g., a rule that would impact a remote town in Alaska with only one
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Appendix D: Public Meeting Notes
employer). In general, EPA asks, "Is there a better technology to remove or
eliminate discharges that do not have non-water quality environmental impacts?"
EPA performs a nationwide analysis of electricity generation for this particular
sector using the Integrated Planning Model (1PM) - Power Sector Model!
EPA. EPA reviews forecasted changes to electricity generation for decades. Other
questions include "Will this result in incremental closure of boilers or entire
plants?" and "How is it impacted by other regulations?" After looking at all
impacts, EPA weighs these factors to make a decision.
• Does the age of the coal-powered plant factor into the regulations and/or rules?
o OW Response: Yes, this is a statutory factor that the Agency must consider.
• What is the timeline for producing and sharing the EPA regulations? Following the
analyses, will there be a compliance deadline or compliance monitoring?
o OW Response: EPA intends to propose a rule by the end of fall 20221 with a final
rule established in 2024. Usually, it takes a few weeks to one month from
signature to publishing as a notice in the Federal Register. EPA typically has a
pre-publication version of the rule available on our website, Steam Electric Power
Generating Effluent Guidelines 1 US EPA, and will post the study reports to the
website. All materials (including analysis results) will be available at
Regulations.gov.
o Following publication of the proposed rule in the Federal Register, a public
comment period begins and typically lasts 90 days. As part of the proposal, EPA
will ask for comments on compliance deadlines and reporting. The ELGs have
some "built-in" monitoring requirements, but there are other pollutants that EPA's
regulatory technologies can control. EPA told community members to feel free to
provide comments on specific pollutants of interest that would help with
transparency and accessibility to data. EPA also asked, "is there something
community members would like to see in the rule regarding information and
access?"
• How do we ensure that the public and utility get notified of the draft rule rather than
reading the FR every day?
o OW Response: EPA strives to be better communicators, such as setting up this
meeting. EPA does not intend on reaching out to each community member but
EPA's main website (I * < nvironmental Protection A.gen»'\ I. c< « ^ \) will have
an announcement and likely information will be sent out to the news media. EPA
encouraged community members to be on the lookout for the proposed rule in late
fall. If individualized outreach would be welcomed, we could look at doing that
(not historically done).
• When the rules/regulations associated with effluent releases are approved, what must the
utility do to comply with the rules/regulations?
1 At the time of the meeting, EPA planned on proposing the supplemental rule by the end of fall. However, the
timing of the rule will likely be winter 2022/2023.
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Appendix D: Public Meeting Notes
o OW Response: These rules are implemented by the state entity through a National
Pollutant Discharge Elimination System (NPDES) permit. In a few exceptions,
EPA is the permitting authority. When the permit is issued, any rule that has been
signed, promulgated, and included in the Code of Federal Regulations (CFR) -
see eCFR :: Title 40 of the CFR — Protection of Environment - the state is
required to include the requirements of the ELGs in the permit. When issued by
the state, permits are open for comment by the public. Regarding the time frame
for the Steam Electric ELGs (40 CFR 423), there may be some lagging permits
not yet up for renewal when the rule is published. States will update the
requirements at the time of the permit renewal — typically a 5-year permit cycle.
Once the permit is in effect, the plant must meet requirements. EPA is looking at
some additional reporting requirements as part of the rule. Note that the permit for
operating landfills is separate from the NPDES permit.
• How will the rules/regulations be influenced by the goal to make substantial reductions in
negative environmental impact by 2030 (as noted in the Inflation Reduction Act (IRA))?
o OW Response: Regarding the greenhouse gas (GHG) reductions, the EPA
Administrator has introduced targets and actions in the IRA. EPA is in the process
of looking at those impacts, and hopefully by the final ELG rule, OW will be able
to take any other actions into account to see impacts in the electricity market. The
Administration is ensuring the rules are harmonized and cumulative impacts are
taken into account, such as unit/plant retirements, economic impacts, pollutant
benefits, energy market.
Receiving Water Characterization
• One of the community members asked about the area of impact that EPA considered,
noting that there is a possibility of tidal flow along the Trout River, and discharges from
Northside Generating Station (Northside) could impact tributaries outside the range
shown in the presentation (1-mile and 3-mile radii). The community member
recommended conducting both a downstream and upstream analysis because the river is
tidally impacted in this area, and the community member personally has conducted
research on the sediment and lower basin of the Trout River directly impacted by
Northside.
o OW Response: EPA noted that the map shown in the presentation was used as
part of the EJ screening analysis to evaluate the demographics around the power
plant to determine if the community had any EJ concerns. In its rulemaking
analysis, EPA is looking beyond those boundaries, including air emission impacts
and impacts to downstream waters (pollutant loadings and health impacts) that
can be as long as 300 kilometers (180 miles) downstream.
EPA noted that this input is helpful to understand the community and the
concerns with specific water bodies. The reverse flow is an aspect that EPA may
want to consider as it could impact fish in different areas not currently considered.
EPA welcomed any research or reports that could be provided or further
D-21
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Appendix D: Public Meeting Notes
discussion that could be via public comments (following rule proposal in the fall)
or a separate meeting.
Environmental. Human Health, and Other Community Concerns
• The community along Trout River is already a heavily impacted socioeconomic
community. Along the Trout River, materials accumulate in the sediment, such as
mercury (see discussion above regarding research).
• Many of the tributaries and the Trout River are impacted by fecal coliform. These areas
are communities with EJ concerns.
o OW Response: EPA's benefits analysis looks at fecal coliform and other
pollutants in the surface water. As noted earlier, EPA may also consider
evaluating the Trout River and upstream impacts.
• The community is concerned with impacts to fish from pollutants discharged by
Northside, along with the air emissions and ash stored at the plant. Community members
asked if EPA would be looking at combined effects of pollutants.
o OW Response: Total cumulative impacts are of interest to the Agency and any
information that community members can provide. The Agency is striving to do
better at cumulative impact assessments. Regarding cross media contamination,
EPA looks at releases to air and water. This ELG rulemaking will have an
assessment of baseline pollutants in the air especially with multiple plants
contributing to an area. EPA is looking where there are multiple pollutants: 1) is
there a joint toxic action documented? 2) are the pollutants synergistic vs.
antagonistic? If there are multiple discharges reaching downstream waters, EPA is
trying to capture the cumulative effects. For a nationwide assessment, it is
challenging to look at all those specific areas. EPA urged attendees to look at the
analyses for the proposed rule once available and provide any comments and
feedback.
o There are also some ongoing EPA air regulations.
• One of the foundations of this area is a thriving fishing community and industry - blue
crab and other seafood. There are many subsistence fishers in the area. Florida residents
consume a higher percentage of fish and thus need greater protection.
o OW Response: When EPA evaluates impacts to human health from fish
consumption, we primarily evaluate four cohorts divided into recreational vs.
subsistence fishers, who have different consumption rates, as well as adult vs.
child consumers. A national analysis will not be as precise regarding fish
consumption in your particular area. It is helpful to know about the economic
significance of the seafood industry.
• Recreational activities, including fishing (several fish camps), marinas, and dining, occur
within sight of the plant. Just outside the 3-mile radius of the plant, the community has
state and city parks where preservation activities and recreational activities occur,
including swimming and walking trails. Community members noted that pollutant
releases from the plant can impact many people.
D-22
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Appendix D: Public Meeting Notes
• Community members noted that a high number of children in the area suffer from
asthma.
• Another concern is that the community is subject to impacts from storm surge during
extreme weather events. The challenges posed by storm surge seem to be increasing.
EPA Analyses for the ELG
• Are you going to do an environmental risk assessment to look at human health and
ecological risk impact? Will it be a site-specific risk assessment?
o OW Response: We perform a nationwide assessment and look at immediate
receiving waters and downstream waters for the four evaluated wastestreams (flue
gas desulfurization wastewater, bottom ash transport water, combustion residual
leachate, and legacy wastewater). Our analysis looks at human health impacts
(non-cancer or cancer impacts) and ecological benchmark exceedances. This is
the same analysis EPA performed for the 2015 and 2020 rules. EPA's assessment
is not akin to Superfund site-specific assessments with monitoring and
environmental sampling. The ELG rules are more of a nationwide focus, but EPA
does incorporate site-based factors into the modeling, including characteristics of
the specific receiving water.
• One attendee asked if EPA would be testing animals (e.g., fish) or water near the plant.
o OW Response: EPA's analysis will look at impacts to humans from the ingestion
of fish at both the immediate receiving water and downstream (i.e., as pollutants
flow down to other water bodies). EPA does not test the wildlife but does assess
exposure to wildlife that eat fish (e.g., mink and eagles). EPA also looks at
impacts to sediment biota and water quality. As noted, the analyses are performed
as a nationwide assessment and not specific to exposure for the Jacksonville
community.
• Another attendee asked if EPA was evaluating both freshwater and marine waterbodies.
o OW Response: EPA has both freshwater and marine National Recommended
Water Quality Criteria (NRWQC) standards: https://www.epa.gov/wqc/national-
recommended-water-qualitv-criteria-tables.1
• Is there a federal maximum daily load for each of the toxins, especially for states like
Florida which don't have maximums? Could this information be included in the report?
o OW Response: EPA does include national criteria (i.e., NRWQC) and other
benchmarks in the analyses, but is unsure whether total maximum daily loads
(TMDLs) are incorporated.2 TMDLs can be allocated across plants, and if
community members have specific knowledge regarding pollutants in the
watershed, EPA can consider the information in any comments that are received
on the rule.
1 EPA's national-scale modeling excludes discharges to estuaries because the specific hydrodynamics and scale of
the analysis required to appropriately model and quantify pollutant concentrations in these types of waterbodies are
more complex than can be represented in the environmental assessment model.
2 EPA does not currently incorporate TMDLs in either the environmental assessment or benefits analysis. TMDLs
are local in nature and scope and would not be included in a national-scale analysis. To conduct local assessments,
EPA would need site-specific data (e.g., hardness, pH, temperature, etc.) from each receiving water.
D-23
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Appendix D: Public Meeting Notes
• One community member noted other resources: 1) CDC website on vulnerable
communities (https://www.cdc.eov/nceh/trackine/topics/PopiilationsVulnerabilities.htm)
and 2) Justice 40 Initiative
(https://www.whitehouse.eov/environmentaliiistice/iiistice40/).
Other Sources of Environmental Pollution in the Area
• Will the study include measures of carbon emissions? And the percentage of total
Jacksonville area carbon emissions from Northside Plant?
o OW Response: Yes, EPA's analyses will look at carbon emissions. The ELG will
not directly impact air emissions; the changes in air emissions are based on shifts
in electricity generation. EPA also sees shifts from high to low carbon emissions.
EPA does not know offhand the percentage of emissions in the area from
Northside, but the relative percentage will be in the record. EPA will have an
index on the website for information, and there will be facility-specific
information in the record.
Information Accessibility and Transparency
• EPA makes greenhouse gas emissions data available to the public through its Flight
database. Does it provide similar public access to data related to liquid pollutant releases
by major facilities? Attendees also have interest in specific information for the Northside
Plant - what pollutants are being evaluated and would be regulated under the new rule?
What are the impacts to health? There is a lot of testing/monitoring but would like
information on compliance by the plant.
o OW Response: The information is available on EPA's Integrated Compliance
Information System (ICIS) website. It is a public facing data source for all major
sources of discharges. The website has all required reporting, including pollutant
concentrations or mass loading, and users can compare to limitations that EPA
has set. There is a tool you can use to look at facilities of interest:
https://echo.epa.eov/trends/loadine4ool/water-pollution-search. EPA maintains
this website to make the information more transparent and accessible.
Note: information on pollutants, including impacts, is available in reports for the
previous rulemakings. See https://www.epa.gov/eg/2020-steam-electric-
recon si derati on -ml e and https://www.epa.gov/ee/steam-electric-power-eeneratine-
effluent-euidelines-2015-final-mle.
Additional Communication
EPA would like to have follow-up communication with the communities. EPA plans on writing a
fact sheet that can be disseminated. Are there ways to improve communication with communities
or ways to present/disseminate information?
• Community members provided contact details for some other community groups of
interest including Jacksonville NAACP and Duval County Soil and Water. Additional
D-24
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Appendix D: Public Meeting Notes
thoughts on communication include reaching out to city council members (email lists of
constituents) and posting flyers for additional meetings.
• Community members noted that regional information in one place on EPA's website
would be helpful.
o OW Response: EPA (HQ) interacts with EPA Regional staff and can pass along
this comment to EPA Region 4 staff (see About EPA Region 4 (Southeast) 1 US
EPA). EPA noted that there is also a website specific to each ELG rulemaking for
the steam electric industry that has details. See links at Steam Ele« >wer
Generating Effluent Guidelines 1 US EPA.
• Community members stated that it is a challenge to reach out to individuals and groups
but noted that explaining information in a simple and easy format and noting the impacts
that occur would be helpful (e.g., to the angling community). The rule itself can be
complicated to convey, and many people do not know what Environmental Justice
means.
• EPA can work with community groups to facilitate the distribution of the fact sheet to
community locations such as state parks or private facilities.
Community members can reach out to EPA for specific information on the rulemaking or EJ
analysis. EPA will hold additional community meetings after the proposal, allowing community
members to review the analyses and provide input. There will be two virtual public meetings
open to any attendee (national level). In addition, EPA would like to continue engagement with
community members located in communities with EJ concerns.
D-25
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Appenci , Distributional Analysis of Neurology i n « • > nitive and Cancer
Impact mi. in Pollutic II • nstream Surface Water Resi ill >
This section of the appendix presents additional results from the distributional analysis of neurological
and cognitive and cancer impacts from exposures to lead, mercury, and arsenic in downstream receiving
waters of steam electric power plants. The results are presented by relevant cohort groups for each
health outcome - child subsistence and recreational fish consumers or adult subsistence and recreational
fish consumers - and by income group - below the poverty line or not below the poverty line -,
controlling for race and ethnicity.
-------
Appendix E: Distributional Analysis of Neurological and Cognitive and Cancer Impacts from Pollution in Downstream Surface Water Results
Table E-l. Modeled Total IQ Points under the Baseline and Change in Avoided IQ Point Losses under the Regulatory Options among Child Subsistence
and Recreational Fish Consumers Exposed to Lead through Fish Consumption, by Income Group, Controlling for Race and Ethnicity
Cohort Group
Race/Ethnic Group
Income Group
Exposed
Populations (a)
Baseline Total IQ Points
(b)
Option 1
Option 2
Option 3
Option 4
White
Below the Poverty Line
6,830(11.8%)
105,916(11.8%)
0
0.00463
0.0194
0.0194
Not Below the Poverty Line
51,132 (88.2%)
791,768 (88.2%)
0
0.0492
0.191
0.191
Black
Below the Poverty Line
3,812 (23.6%)
59,436.7(23.7%)
0.138
0.149
0.335
0.336
Note Below the Poverty Line
12,312(76.4%)
191,804 (76.3%)
0.619
0.736
1.66
1.67
Hispanic
Below the Poverty Line
827(17.8%)
13,070.6(17.8%)
0
0.00264
0.0167
0.0167
Child Subsistence
Not Below the Poverty Line
3,825 (82.2%)
60,412.5 ( 82.2%)
0
0.0151
0.06732
0.0674
Asian
Below the Poverty Line
365 (11.1%)
5,885.18(11.1%)
0
0.000240
0.0104
0.0105
Not Below the Poverty Line
2,917(88.9%)
46,904.3 (88.9%)
0
0.00290
0.0647
0.0652
American Indian and Alaska
Below the Poverty Line
104 (21.6%)
1,686.93 (21.6%)
0
0.0000100
0.0163
0.0163
Native
Not Below the Poverty Line
380 (78.4%)
6,108.67(78.4%)
0
0.000110
0.0414
0.0414
Other
Below the Poverty Line
384(15.7%)
6,195.62 (15.7%)
0
0.000130
0.00574
0.00588
Not Below the Poverty Line
2,063 (84.3%)
33,195.11 (84.3%)
0
0.000550
0.0242
0.0248
White
Below the Poverty Line
99,542 (11.8%)
1,498,230 (11.8%)_
0
0.0217
0.0300
0.0300
Not Below the Poverty Line
745,153 (88.2%)
11,197,400(88.2%)
0
0.207
0.572
0.572
Black
Below the Poverty Line
55,555 (23.6%)
839,103 (23.7%)
0
0
0.00182
0.00182
Not Below the Poverty Line
179,425 (76.4%)
2,707,350 (76.3%)
0
0
0.0633
0.0633
Hispanic
Below the Poverty Line
12,052 (17.8%)
182,396(17.8%)
0
0.0405
0.141
0.141
Child Recreation
Not Below the Poverty Line
55,754 (82.2%)
842,841 (82.2%)
0
0.136
0.750
0.750
Asian
Below the Poverty Line
5,323 (11.1%)
80,818.1 (11.2%)
0
0.00812
0.0431
0.0431
Not Below the Poverty Line
42,519(88.9%)
643,641 (88.8%)
0
0.0570
0.649
0.649
American Indian and Alaska
Below the Poverty Line
1,527(21.6%)
23,156.0 (21.6%)
0
0.000910
0.00439
0.00439
Native
Not Below the Poverty Line
5,538 (78.4%)
83,839.5 (78.4%)
0
0.00147
0.0247
0.0247
Other
Below the Poverty Line
5,604(15.7%)
85,083.30(15.7%)
0
0.00274
0.0196
0.0196
Not Below the Poverty Line
30,065 (84.3%)
455,660.34 (84.3%)
0
0.00809
0.211
0.211
Notes:
(a) The exposed population for each race and ethnic group and income group is presented as the number of people exposed and the number of people exposed as a share of the total exposed population
for the relevant income group in the cohort (in parentheses).
(b) Hie baseline total IQ points for each race and ethnic group and income group are presented as the total number of IQ points and the total number of IQ points as a share of the total number of IQ
points for the relevant income group in the cohort (in parentheses).
E-l
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Appendix E: Distributional Analysis of Neurological and Cognitive and Cancer Impacts from Pollution in Downstream Surface Water Results
Table E-2. Modeled Total IQ Points under the Baseline and Change in Avoided IQ Point Losses under the Regulatory Options among Child Subsistence
and Recreational Fish Consumers Exposed to Mercury through Fish Consumption, by Income Group, Controlling for Race and Ethnicity
Cohort Group
Race/Ethnic Group
Income Group
Exposed
Population (a)
Baseline Total IQ Points
(b)
Option 1
Option 2
Option 3
Option 4
White
Below the Poverty Line
943 (12.8%)
5,900.27 (12.8%)
53.3
53.9
54.8
54.8
Not Below the Poverty Line
6,451 (87.2%)
40,285.7 (87.2%)
311
315
321
322
Black
Below the Poverty Line
492 (21.9%)
3,392.34 (21.9%)
25.3
25.5
26.2
26.2
Note Below the Poverty Line
1,756 (78.1%)
12,104.5 (78.1%)
84.2
85.4
88.3
88.4
Hispanic
Below the Poverty Line
113 (17.1%)
1,008.24 (17.1%)
6.56
6.73
7.19
7.19
Child Subsistence
Not Below the Poverty Line
552 (82.9%)
4,899.34 (82.9%)
30.4
31.1
33.2
33.2
Asian
Below the Poverty Line
63 (13.8%)
745.160 (13.8%)
4.77
4.88
5.12
5.13
Not Below the Poverty Line
394 (86.2%)
4,662.71 (86.2%)
23.7
24.4
26.4
26.4
American Indian and Alaska Native
Below the Poverty Line
12 (20.7%)
142.110 (20.7%)
0.580
0.590
0.760
0.760
Not Below the Poverty Line
46 (79.3%)
543.670 (79.3%)
2.35
2.40
2.89
2.89
Other
Below the Poverty Line
51 (15.9%)
608.470 (15.9%)
4.98
5.04
5.16
5.16
Not Below the Poverty Line
271 (84.1%)
3,210.33 (84.1%)
22.4
22.8
23.4
23.5
White
Below the Poverty Line
13,747 (12.8%)
30,320.9 (12.8%)
274
277
281
282
Not Below the Poverty Line
94,016 (87.2%)
207,024 (87.2%)
1,600
1,620
1,650
1,650
Black
Below the Poverty Line
7,171 (21.9%)
18,126.8 (21.9%)
135
136
140
140
Not Below the Poverty Line
25,597 (78.1%)
64,679.7 (78.1%)
450
456
472
472
Hispanic
Below the Poverty Line
1,656 (17.1%)
4,462.33 (17.1%)
29.1
29.8
31.8
31.8
Child Recreation
Not Below the Poverty Line
8,050 (82.9%)
21,683.9 (82.9%)
135
138
147
147
Asian
Below the Poverty Line
918 (13.8%)
2,895.79 (13.8%)
18.5
19.0
19.9
19.9
Not Below the Poverty Line
5,755 (86.2%)
18,119.9 (86.2%)
92.1
94.9
103
103
American Indian and Alaska Native
Below the Poverty Line
176 (20.7%)
552.250 (20.7%)
2.25
2.29
2.96
2.97
Not Below the Poverty Line
676 (79.3%)
2,112.79 (79.3%)
9.13
9.33
11.2
11.3
Other
Below the Poverty Line
749 (15.9%)
2,364.58 (15.9%)
19.4
19.6
20.1
20.1
Not Below the Poverty Line
3,961 (84.1%)
12,475.8 (84.1%)
87.1
88.4
91.1
91.1
Notes:
(a) The exposed population for each race and ethnic group and income group is presented as the number of people exposed and the number of people exposed as a share of the total exposed population
for the relevant income group in the cohort (in parentheses).
(b) Hie baseline total IQ points for each race and ethnic group and income group are presented as the total number of IQ points and the total number of IQ points as a share of the total number of IQ
points for the relevant income group in the cohort (in parentheses).
E-2
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Appendix E: Distributional Analysis of Neurological and Cognitive and Cancer Impacts from Pollution in Downstream Surface Water Results
Table E-3. Modeled Total Cancer Cases under the Baseline and Change in Avoided Cancer Cases under the Regulatory Options among Adult
Subsistence and Recreational Fish Consumers Exposed to Arsenic through Fish Consumption, by Income Group, Controlling for Race and Ethnicity
Cohort Group
Race/Ethnic Group
Income Group
Exposed Population
Total Cancer
Cases
Option 1
Option 2
Option 3
Option 4
Below the Poverty Line
82,136 (11.5%)
4.57 (11.2%)
0.000199
0.000202
0.000206
0.000206
White
Not Below the Poverty Line
632,442 (88.5%)
36.1 (88.8%)
0.00115
0.00117
0.00121
0.00121
Black
Below the Poverty Line
36,094 (21.1%)
2.12 (20.4%)
0.0000490
0.0000502
0.0000524
0.0000525
Note Below the Poverty Line
134,987 (78.9%)
8.30 (79.6%)
0.000174
0.000179
0.000190
0.000190
Hispanic
Below the Poverty Line
7,743 (16.2%)
0.583 (15.6%)
0.0000104
0.0000111
0.0000126
0.0000126
Adult Subsistence
Not Below the Poverty Line
40,196 (83.8%)
3.15 (84.4%)
0.0000533
0.0000565
0.0000635
0.0000636
Asian
Below the Poverty Line
4,415 (11.6%)
0.45 (11.2%)
0.00000847
0.00000894
0.00000988
0.00000989
Not Below the Poverty Line
33,570 (88.4%)
3.56 (88.8%)
0.0000530
0.0000569
0.0000652
0.0000653
American Indian and
Below the Poverty Line
1,061 (19.8%)
0.107 (19.3%)
0.00000167
0.00000173
0.00000247
0.00000248
Alaska Native
Not Below the Poverty Line
4,291 (80.2%)
0.448 (80.7%)
0.00000653
0.00000688
0.00000905
0.00000906
Other
Below the Poverty Line
3,921 (14.6%)
0.399 (14.1%)
0.0000125
0.0000128
0.0000133
0.0000133
Not Below the Poverty Line
22,916 (85.4%)
2.42 (85.9%)
0.0000585
0.0000604
0.0000632
0.0000633
White
Below the Poverty Line
1,196,969 (11.5%)
23.5 (11.2%)
0.00102
0.00104
0.00106
0.00106
Not Below the Poverty Line
9,216,588 (88.5%)
185 (88.8%)
0.00591
0.00604
0.00620
0.00621
Black
Below the Poverty Line
526,000 (21.1%)
11.3 (20.4%)
0.000262
0.000268
0.000280
0.000281
Not Below the Poverty Line
1,967,172 (78.9%)
44.3 (79.6%)
0.000928
0.000958
0.00101
0.00102
Hispanic
Below the Poverty Line
112,845 (16.2%)
2.58 (15.6%)
0.0000461
0.0000490
0.0000556
0.0000557
Adult Recreation
Not Below the Poverty Line
585,788 (83.8%)
14.0 (84.4%)
0.000236
0.000250
0.000281
0.000282
Asian
Below the Poverty Line
64,346 (11.6%)
1.75 (11.2%)
0.0000329
0.0000348
0.0000384
0.0000384
Not Below the Poverty Line
489,221 (88.4%)
13.9 (88.8%)
0.000206
0.000221
0.000253
0.000254
American Indian and
Alaska Native
Below the Poverty Line
15,468 (19.8%)
0.415 (19.3%)
0.00000649
0.00000673
0.00000961
0.00000962
Not Below the Poverty Line
62,538 (80.2%)
1.74 (80.7%)
0.0000254
0.0000267
0.0000352
0.0000352
Other
Below the Poverty Line
57,143 (14.6%)
1.55 (14.1%)
0.0000486
0.0000498
0.0000515
0.0000516
Not Below the Poverty Line
333,968 (85.4%)
9.41 (85.9%)
0.000227
0.000235
0.000246
0.000246
Notes:
(a) The exposed population for each race and ethnic group and income group is presented as the number of people exposed and the number of people exposed as a share of the total exposed population
for the relevant income group in the cohort (in parentheses).
(b) Hie baseline total cancer cases for each race and ethnic group and income group are presented as the total number of cancer cases and the total number of cancer cases as a share of the total
number of cancer cases for the relevant income group in the cohort (in parentheses).
E-3
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